Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Mon, 15 Dec 2014 10:41:33 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418640159xp03mtz5bqrr250.htm/, Retrieved Thu, 16 May 2024 20:06:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268065, Retrieved Thu, 16 May 2024 20:06:29 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Multiple Regression] [] [2013-11-04 07:18:26] [0307e7a6407eb638caabc417e3a6b260]
- RMPD  [Multiple Regression] [] [2014-11-13 18:59:36] [95c11abf048d3a1e472aeccb09199113]
-    D    [Multiple Regression] [] [2014-11-13 19:46:46] [95c11abf048d3a1e472aeccb09199113]
-    D        [Multiple Regression] [] [2014-12-15 10:41:33] [4bf1efda48b6e8e35beb7b429a900cbb] [Current]
- R PD          [Multiple Regression] [] [2014-12-15 11:11:17] [2fea329c6e322b1612c5dc504f90c0ef] 
- R PD          [Multiple Regression] [] [2014-12-15 11:15:41] [2fea329c6e322b1612c5dc504f90c0ef] 
- R PD          [Multiple Regression] [] [2014-12-15 11:20:26] [2fea329c6e322b1612c5dc504f90c0ef] 
- R PD          [Multiple Regression] [] [2014-12-15 11:21:52] [2fea329c6e322b1612c5dc504f90c0ef] 

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

7,5	21	11	8	7	18	12	20	4	149	96	18	68	86
2,5	26	15	18	18	23	20	25	9	152	75	7	55	62
6,0	22	19	18	20	23	20	19	4	139	70	31	39	70
6,5	22	16	12	9	22	14	18	5	148	88	39	32	71
1,0	18	24	24	19	22	25	24	4	158	114	46	62	108
1,0	23	15	16	12	19	15	20	4	128	69	31	33	64
5,5	12	17	19	16	25	20	20	9	224	176	67	52	119
8,5	20	19	16	17	28	21	24	8	159	114	35	62	97
6,5	22	19	15	9	16	15	21	11	105	121	52	77	129
4,5	21	28	28	28	28	28	28	4	159	110	77	76	153
2,0	19	26	21	20	21	11	10	4	167	158	37	41	78
5,0	22	15	18	16	22	22	22	6	165	116	32	48	80
0,5	15	26	22	22	24	22	19	4	159	181	36	63	99
5,0	20	16	19	17	24	27	27	8	119	77	38	30	68
5,0	19	24	22	12	26	24	23	4	176	141	69	78	147
2,5	18	25	25	18	28	23	24	4	54	35	21	19	40
5,0	15	22	20	20	24	24	24	11	91	80	26	31	57
5,5	20	15	16	12	20	21	25	4	163	152	54	66	120
3,5	21	21	19	16	26	20	24	4	124	97	36	35	71
3,0	21	22	18	16	21	19	21	6	137	99	42	42	84
4,0	15	27	26	21	28	25	28	6	121	84	23	45	68
0,5	16	26	24	15	27	16	28	4	153	68	34	21	55
6,5	23	26	20	17	23	24	22	8	148	101	112	25	137
4,5	21	22	19	17	24	21	26	5	221	107	35	44	79
7,5	18	21	19	17	24	22	26	4	188	88	47	69	116
5,5	25	22	23	18	22	25	21	9	149	112	47	54	101
4,0	9	20	18	15	21	23	26	4	244	171	37	74	111
7,5	30	21	16	20	25	20	23	7	148	137	109	80	189
7,0	20	20	18	13	20	21	20	10	92	77	24	42	66
4,0	23	22	21	21	21	22	24	4	150	66	20	61	81
5,5	16	21	20	12	26	25	25	4	153	93	22	41	63
2,5	16	8	15	6	23	23	24	7	94	105	23	46	69
5,5	19	22	19	13	21	19	20	12	156	131	32	39	71
0,5	25	18	27	6	27	27	23	4	146	89	7	63	70
3,5	25	20	19	19	27	21	24	7	132	102	30	34	64
2,5	18	24	7	12	25	19	25	5	161	161	92	51	143
4,5	23	17	20	14	23	25	23	8	105	120	43	42	85
4,5	21	20	20	13	25	16	21	5	97	127	55	31	86
4,5	10	23	19	12	23	24	23	4	151	77	16	39	55
6,0	14	20	19	17	19	24	21	9	131	108	49	20	69
2,5	22	22	20	19	22	18	18	7	166	85	71	49	120
5,0	26	19	18	10	24	28	24	4	157	168	43	53	96
0,0	23	15	14	10	19	15	18	4	111	48	29	31	60
5,0	23	20	17	11	21	17	21	4	145	152	56	39	95
6,5	24	22	17	11	27	18	23	4	162	75	46	54	100
5,0	24	17	8	10	25	26	25	4	163	107	19	49	68
6,0	18	14	9	7	25	18	22	7	59	62	23	34	57
4,5	23	24	22	22	23	22	22	4	187	121	59	46	105
5,5	15	17	20	12	17	19	23	7	109	124	30	55	85
1,0	19	23	20	18	28	17	24	4	90	72	61	42	103
7,5	16	25	22	20	25	26	25	4	105	40	7	50	57
6,0	25	16	22	9	20	21	22	4	83	58	38	13	51
5,0	23	18	22	16	25	26	24	4	116	97	32	37	69
1,0	17	20	16	14	21	21	21	8	42	88	16	25	41
5,0	19	18	14	11	24	12	24	4	148	126	19	30	49
6,5	21	23	24	20	28	20	25	4	155	104	22	28	50
7,0	18	24	21	17	20	20	23	4	125	148	48	45	93
4,5	27	23	20	14	19	24	27	4	116	146	23	35	58
0,0	21	13	20	8	24	24	27	7	128	80	26	28	54
8,5	13	20	18	16	21	22	23	12	138	97	33	41	74
3,5	8	20	14	11	24	21	18	4	49	25	9	6	15
7,5	29	19	19	10	23	20	20	4	96	99	24	45	69
3,5	28	22	24	15	18	23	23	4	164	118	34	73	107
6,0	23	22	19	15	27	19	24	5	162	58	48	17	65
1,5	21	15	16	10	25	24	26	15	99	63	18	40	58
9,0	19	17	16	10	20	21	20	5	202	139	43	64	107
3,5	19	19	16	18	21	16	23	10	186	50	33	37	70
3,5	20	20	14	10	23	17	22	9	66	60	28	25	53
4,0	18	22	22	22	27	23	23	8	183	152	71	65	136
6,5	19	21	21	16	24	20	17	4	214	142	26	100	126
7,5	17	21	15	10	27	19	20	5	188	94	67	28	95
6,0	19	16	14	7	24	18	22	4	104	66	34	35	69
5,0	25	20	15	16	23	18	18	9	177	127	80	56	136
5,5	19	21	14	16	24	21	19	4	126	67	29	29	58
3,5	22	20	20	16	21	20	19	10	76	90	16	43	59
7,5	23	23	21	22	23	17	16	4	99	75	59	59	118
1,0	26	15	17	13	22	20	24	7	157	96	58	52	110
6,5	14	18	14	5	27	25	26	4	139	128	32	50	82
NA	28	22	19	18	24	15	14	6	78	41	47	3	50
6,5	16	16	16	10	25	17	25	7	162	146	43	59	102
6,5	24	17	13	8	19	17	23	5	108	69	38	27	65
7,0	20	24	26	16	24	24	18	4	159	186	29	61	90
3,5	12	13	13	8	25	21	22	4	74	81	36	28	64
1,5	24	19	18	16	23	22	26	4	110	85	32	51	83
4,0	22	20	15	14	23	18	25	4	96	54	35	35	70
7,5	12	22	18	15	25	22	26	4	116	46	21	29	50
4,5	22	19	21	9	26	20	26	4	87	106	29	48	77
0,0	20	21	17	21	26	21	24	6	97	34	12	25	37
3,5	10	15	18	7	16	21	22	10	127	60	37	44	81
5,5	23	21	20	17	23	20	21	7	106	95	37	64	101
5,0	17	24	18	18	26	18	22	4	80	57	47	32	79
4,5	22	22	25	16	25	25	28	4	74	62	51	20	71
2,5	24	20	20	16	23	23	22	7	91	36	32	28	60
7,5	18	21	19	14	26	21	26	4	133	56	21	34	55
7,0	21	19	18	15	22	20	20	8	74	54	13	31	44
0,0	20	14	12	8	20	21	24	11	114	64	14	26	40
4,5	20	25	22	22	27	20	21	6	140	76	-2	58	56
3,0	22	11	16	5	20	22	23	14	95	98	20	23	43
1,5	19	17	18	13	22	15	23	5	98	88	24	21	45
3,5	20	22	23	22	24	24	23	4	121	35	11	21	32
2,5	26	20	20	18	21	22	22	8	126	102	23	33	56
5,5	23	22	20	15	24	21	23	9	98	61	24	16	40
8,0	24	15	16	11	26	17	21	4	95	80	14	20	34
1,0	21	23	22	19	24	23	27	4	110	49	52	37	89
5,0	21	20	19	19	24	22	23	5	70	78	15	35	50
4,5	19	22	23	21	27	23	26	4	102	90	23	33	56
3,0	8	16	6	4	25	16	27	5	86	45	19	27	46
3,0	17	25	19	17	27	18	27	4	130	55	35	41	76
8,0	20	18	24	10	19	25	23	4	96	96	24	40	64
2,5	11	19	19	13	22	18	23	7	102	43	39	35	74
7,0	8	25	15	15	22	14	23	10	100	52	29	28	57
0,0	15	21	18	11	25	20	28	4	94	60	13	32	45
1,0	18	22	18	20	23	19	24	5	52	54	8	22	30
3,5	18	21	22	13	24	18	20	4	98	51	18	44	62
5,5	19	22	23	18	24	22	23	4	118	51	24	27	51
5,5	19	23	18	20	23	21	22	4	99	38	19	17	36
0,5	23	20	17	15	22	14	15	6	48	41	23	12	34
7,5	22	6	6	4	24	5	27	4	50	146	16	45	61
9	21	15	22	9	19	25	23	8	150	182	33	37	70
9,5	25	18	20	18	25	21	23	5	154	192	32	37	69
8,5	30	24	16	12	26	11	20	4	109	263	37	108	145
7	17	22	16	17	18	20	18	17	68	35	14	10	23
8	27	21	17	12	24	9	22	4	194	439	52	68	120
10	23	23	20	16	28	15	20	4	158	214	75	72	147
7	23	20	23	17	23	23	21	8	159	341	72	143	215
8,5	18	20	18	14	19	21	25	4	67	58	15	9	24
9	18	18	13	13	19	9	19	7	147	292	29	55	84
9,5	23	25	22	20	27	24	25	4	39	85	13	17	30
4	19	16	20	16	24	16	24	4	100	200	40	37	77
6	15	20	20	15	26	20	22	5	111	158	19	27	46
8	20	14	13	10	21	15	28	7	138	199	24	37	61
5,5	16	22	16	16	25	18	22	4	101	297	121	58	178
9,5	24	26	25	21	28	22	21	4	131	227	93	66	160
7,5	25	20	16	15	19	21	23	7	101	108	36	21	57
7	25	17	15	16	20	21	19	11	114	86	23	19	42
7,5	19	22	19	19	26	21	21	7	165	302	85	78	163
8	19	22	19	9	27	20	25	4	114	148	41	35	75
7	16	20	24	19	23	24	23	4	111	178	46	48	94
7	19	17	9	7	18	15	28	4	75	120	18	27	45
6	19	22	22	23	23	24	14	4	82	207	35	43	78
10	23	17	15	14	21	18	23	4	121	157	17	30	47
2,5	21	22	22	10	23	24	24	4	32	128	4	25	29
9	22	21	22	16	22	24	25	6	150	296	28	69	97
8	19	25	24	12	21	15	15	8	117	323	44	72	116
6	20	11	12	10	14	19	23	23	71	79	10	23	32
8,5	20	19	21	7	24	20	26	4	165	70	38	13	50
6	3	24	25	20	26	26	21	8	154	146	57	61	118
9	23	17	26	9	24	26	26	6	126	246	23	43	66
8	14	22	19	14	26	18	15	4	138	145	26	22	48
8	23	22	21	12	22	23	23	4	149	196	36	51	86
9	20	17	14	10	20	13	15	7	145	199	22	67	89
5,5	15	26	28	19	20	16	16	4	120	127	40	36	76
5	13	19	16	16	20	19	20	4	138	91	18	21	39
7	16	20	21	11	18	22	20	4	109	153	31	44	75
5,5	7	19	16	15	18	21	20	4	132	299	11	45	57
9	24	21	16	14	25	11	21	10	172	228	38	34	72
2	17	24	25	11	28	23	28	6	169	190	24	36	60
8,5	24	21	21	14	23	18	19	5	114	180	37	72	109
9	24	19	22	15	20	19	21	5	156	212	37	39	76
8,5	19	13	9	7	22	15	22	4	172	269	22	43	65
9	25	24	20	22	27	8	27	4	68	130	15	25	40
7,5	20	28	19	19	24	15	20	5	89	179	2	56	58
10	28	27	24	22	23	21	17	5	167	243	43	80	123
9	23	22	22	11	20	25	26	5	113	190	31	40	71
7,5	27	23	22	19	22	14	21	5	115	299	29	73	102
6	18	19	12	9	21	21	24	4	78	121	45	34	80
10,5	28	18	17	11	24	18	21	6	118	137	25	72	97
8,5	21	23	18	17	26	18	25	4	87	305	4	42	46
8	19	21	10	12	24	12	22	4	173	157	31	61	93
10	23	22	22	17	18	24	17	4	2	96	-4	23	19
10,5	27	17	24	10	17	17	14	9	162	183	66	74	140
6,5	22	15	18	17	23	20	23	18	49	52	61	16	78
9,5	28	21	18	13	21	24	28	6	122	238	32	66	98
8,5	25	20	23	11	21	22	24	5	96	40	31	9	40
7,5	21	26	21	19	24	15	22	4	100	226	39	41	80
5	22	19	21	21	22	22	24	11	82	190	19	57	76
8	28	28	28	24	24	26	25	4	100	214	31	48	79
10	20	21	17	13	24	17	21	10	115	145	36	51	87
7	29	19	21	16	24	23	22	6	141	119	42	53	95
7,5	25	22	21	13	23	19	16	8	165	222	21	29	49
7,5	25	21	20	15	21	21	18	8	165	222	21	29	49
9,5	20	20	18	15	24	23	27	6	110	159	25	55	80
6	20	19	17	11	19	19	17	8	118	165	32	54	86
10	16	11	7	7	19	18	25	4	158	249	26	43	69
7	20	17	17	13	23	16	24	4	146	125	28	51	79
3	20	19	14	13	25	23	21	9	49	122	32	20	52
6	23	20	18	12	24	13	21	9	90	186	41	79	120
7	18	17	14	8	21	18	19	5	121	148	29	39	69
10	25	21	23	7	18	23	27	4	155	274	33	61	94
7	18	21	20	17	23	21	28	4	104	172	17	55	72
3,5	19	12	14	9	20	23	19	15	147	84	13	30	43
8	25	23	17	18	23	16	23	10	110	168	32	55	87
10	25	22	21	17	23	17	25	9	108	102	30	22	52
5,5	25	22	23	17	23	20	26	7	113	106	34	37	71
6	24	21	24	18	23	18	25	9	115	2	59	2	61
6,5	19	20	21	12	27	20	25	6	61	139	13	38	51
6,5	26	18	14	14	19	19	24	4	60	95	23	27	50
8,5	10	21	24	22	25	26	24	7	109	130	10	56	67
4	17	24	16	19	25	9	24	4	68	72	5	25	30
9,5	13	22	21	21	21	23	22	7	111	141	31	39	70
8	17	20	8	10	25	9	21	4	77	113	19	33	52
8,5	30	17	17	16	17	13	17	15	73	206	32	43	75
5,5	25	19	18	11	22	27	23	4	151	268	30	57	87
7	4	16	17	15	23	22	17	9	89	175	25	43	69
9	16	19	16	12	27	12	25	4	78	77	48	23	72
8	21	23	22	21	27	18	19	4	110	125	35	44	79
10	23	8	17	22	5	6	8	28	220	255	67	54	121
8	22	22	21	20	19	17	14	4	65	111	15	28	43
6	17	23	20	15	24	22	22	4	141	132	22	36	58
8	20	15	20	9	23	22	25	4	117	211	18	39	57
5	20	17	19	15	28	23	28	5	122	92	33	16	50
9	22	21	8	14	25	19	25	4	63	76	46	23	69
4,5	16	25	19	11	27	20	24	4	44	171	24	40	64
8,5	23	18	11	9	16	17	15	12	52	83	14	24	38
7	16	23	15	18	23	18	25	5	62	119	23	29	53
9,5	0	20	13	12	25	24	24	4	131	266	12	78	90
8,5	18	21	18	11	26	20	28	6	101	186	38	57	96
7,5	25	21	19	14	24	18	24	6	42	50	12	37	49
7,5	23	24	23	10	23	23	25	5	152	117	28	27	56
5	12	22	20	18	24	27	23	4	107	219	41	61	102
7	18	22	22	11	27	25	26	4	77	246	12	27	40
8	24	23	19	14	25	24	26	4	154	279	31	69	100
5,5	11	17	16	16	19	12	22	10	103	148	33	34	67
8,5	18	15	11	11	19	16	25	7	96	137	34	44	78
7,5	14	24	11	8	14	16	20	4	154	130	41	21	62
9,5	23	22	21	16	24	24	22	4	175	181	21	34	55
7	24	19	14	13	20	23	26	7	57	98	20	39	59
8	29	18	21	12	21	24	20	4	112	226	44	51	96
8,5	18	21	20	17	28	24	26	4	143	234	52	34	86
3,5	15	20	21	23	26	26	26	12	49	138	7	31	38
6,5	29	19	20	14	19	19	21	5	110	85	29	13	43
6,5	16	19	19	10	23	28	21	8	131	66	11	12	23
10,5	19	16	19	16	23	23	24	6	167	236	26	51	77
8,5	22	18	18	11	21	21	21	17	56	106	24	24	48
8	16	23	20	16	26	19	18	4	137	135	7	19	26
10	23	22	21	19	25	23	23	5	86	122	60	30	91
10	23	23	22	17	25	23	26	4	121	218	13	81	94
9,5	19	20	19	12	24	20	23	5	149	199	20	42	62
9	4	24	23	17	23	18	25	5	168	112	52	22	74
10	20	25	16	11	22	20	20	6	140	278	28	85	114
7,5	24	25	23	19	27	28	25	4	88	94	25	27	52
4,5	20	20	18	12	26	21	26	4	168	113	39	25	64
4,5	4	23	23	8	23	25	19	4	94	84	9	22	31
0,5	24	21	20	17	22	18	21	6	51	86	19	19	38
6,5	22	23	20	13	26	24	23	8	48	62	13	14	27
4,5	16	23	23	17	22	28	24	10	145	222	60	45	105
5,5	3	11	13	7	17	9	6	4	66	167	19	45	64
5	15	21	21	23	25	22	22	5	85	82	34	28	62
6	24	27	26	18	22	26	21	4	109	207	14	51	65
4	17	19	18	13	28	28	28	4	63	184	17	41	58
8	20	21	19	17	22	18	24	4	102	83	45	31	76
10,5	27	16	18	13	21	23	14	16	162	183	66	74	140
8,5	23	22	19	13	21	22	17	4	128	85	24	24	48
6,5	26	21	18	8	24	15	20	7	86	89	48	19	68
8	23	22	19	16	26	24	28	4	114	225	29	51	80
8,5	17	16	13	14	26	12	19	4	164	237	-2	73	71
5,5	20	18	10	13	24	12	24	14	119	102	51	24	76
7	22	23	21	19	27	20	21	5	126	221	2	61	63
5	19	24	24	15	22	25	21	5	132	128	24	23	46
3,5	24	20	21	15	23	24	26	5	142	91	40	14	53
5	19	20	23	8	22	23	24	5	83	198	20	54	74
9	23	18	18	14	23	18	26	7	94	204	19	51	70
8,5	15	4	11	7	15	20	25	19	81	158	16	62	78
5	27	14	16	11	20	22	23	16	166	138	20	36	56
9,5	26	22	20	17	22	20	24	4	110	226	40	59	100
3	22	17	20	19	25	25	24	4	64	44	27	24	51
1,5	22	23	26	17	27	28	26	7	93	196	25	26	52
6	18	20	21	12	24	25	23	9	104	83	49	54	102
0,5	15	18	12	12	21	14	20	5	105	79	39	39	78
6,5	22	19	15	18	17	16	16	14	49	52	61	16	78
7,5	27	20	18	16	26	24	24	4	88	105	19	36	55
4,5	10	15	14	15	20	13	20	16	95	116	67	31	98
8	20	24	18	20	22	19	23	10	102	83	45	31	76
9	17	21	16	16	24	18	23	5	99	196	30	42	73
7,5	23	19	19	12	23	16	18	6	63	153	8	39	47
8,5	19	19	7	10	22	8	21	4	76	157	19	25	45
7	13	27	21	28	28	27	25	4	109	75	52	31	83
9,5	27	23	24	19	21	23	23	4	117	106	22	38	60
6,5	23	23	21	18	24	20	26	5	57	58	17	31	48
9,5	16	20	20	19	28	20	26	4	120	75	33	17	50
6	25	17	22	8	25	26	24	4	73	74	34	22	56
8	2	21	17	17	24	23	23	5	91	185	22	55	77
9,5	26	23	19	16	24	24	21	4	108	265	30	62	91
8	20	22	20	18	21	21	23	4	105	131	25	51	76
8	23	16	16	12	20	15	20	5	117	139	38	30	68
9	22	20	20	17	26	22	23	8	119	196	26	49	74
5	24	16	16	13	16	25	24	15	31	78	13	16	29

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	12 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268065&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268065&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268065&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	12 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Multiple Linear Regression - Estimated Regression Equation
examenscore[t] = + 4.84357 + 0.0610439numeracy_tot[t] + 0.0745865I1[t] -0.0620302I2[t] + 0.00502049I3[t] -0.0574701E1[t] -0.0142867E2[t] -0.0243797E3[t] + 0.0151911A[t] -0.000692744LFM[t] + 0.0172191B[t] -0.519251PRH[t] -0.521445CH[t] + 0.513809H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
examenscore[t] =  +  4.84357 +  0.0610439numeracy_tot[t] +  0.0745865I1[t] -0.0620302I2[t] +  0.00502049I3[t] -0.0574701E1[t] -0.0142867E2[t] -0.0243797E3[t] +  0.0151911A[t] -0.000692744LFM[t] +  0.0172191B[t] -0.519251PRH[t] -0.521445CH[t] +  0.513809H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268065&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]examenscore[t] =  +  4.84357 +  0.0610439numeracy_tot[t] +  0.0745865I1[t] -0.0620302I2[t] +  0.00502049I3[t] -0.0574701E1[t] -0.0142867E2[t] -0.0243797E3[t] +  0.0151911A[t] -0.000692744LFM[t] +  0.0172191B[t] -0.519251PRH[t] -0.521445CH[t] +  0.513809H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268065&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268065&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
examenscore[t] = + 4.84357 + 0.0610439numeracy_tot[t] + 0.0745865I1[t] -0.0620302I2[t] + 0.00502049I3[t] -0.0574701E1[t] -0.0142867E2[t] -0.0243797E3[t] + 0.0151911A[t] -0.000692744LFM[t] + 0.0172191B[t] -0.519251PRH[t] -0.521445CH[t] + 0.513809H[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	4.84357	1.72036	2.815	0.00522732	0.00261366
numeracy_tot	0.0610439	0.027364	2.231	0.0265092	0.0132546
I1	0.0745865	0.0549343	1.358	0.175671	0.0878357
I2	-0.0620302	0.0483463	-1.283	0.20057	0.100285
I3	0.00502049	0.0411498	0.122	0.902985	0.451493
E1	-0.0574701	0.0559826	-1.027	0.305535	0.152767
E2	-0.0142867	0.039977	-0.3574	0.72109	0.360545
E3	-0.0243797	0.0472352	-0.5161	0.606181	0.30309
A	0.0151911	0.048301	0.3145	0.753376	0.376688
LFM	-0.000692744	0.00405671	-0.1708	0.864535	0.432268
B	0.0172191	0.00245926	7.002	1.97777e-11	9.88886e-12
PRH	-0.519251	0.376094	-1.381	0.168522	0.0842609
CH	-0.521445	0.375512	-1.389	0.166083	0.0830417
H	0.513809	0.375348	1.369	0.172164	0.0860819

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 4.84357 & 1.72036 & 2.815 & 0.00522732 & 0.00261366 \tabularnewline
numeracy_tot & 0.0610439 & 0.027364 & 2.231 & 0.0265092 & 0.0132546 \tabularnewline
I1 & 0.0745865 & 0.0549343 & 1.358 & 0.175671 & 0.0878357 \tabularnewline
I2 & -0.0620302 & 0.0483463 & -1.283 & 0.20057 & 0.100285 \tabularnewline
I3 & 0.00502049 & 0.0411498 & 0.122 & 0.902985 & 0.451493 \tabularnewline
E1 & -0.0574701 & 0.0559826 & -1.027 & 0.305535 & 0.152767 \tabularnewline
E2 & -0.0142867 & 0.039977 & -0.3574 & 0.72109 & 0.360545 \tabularnewline
E3 & -0.0243797 & 0.0472352 & -0.5161 & 0.606181 & 0.30309 \tabularnewline
A & 0.0151911 & 0.048301 & 0.3145 & 0.753376 & 0.376688 \tabularnewline
LFM & -0.000692744 & 0.00405671 & -0.1708 & 0.864535 & 0.432268 \tabularnewline
B & 0.0172191 & 0.00245926 & 7.002 & 1.97777e-11 & 9.88886e-12 \tabularnewline
PRH & -0.519251 & 0.376094 & -1.381 & 0.168522 & 0.0842609 \tabularnewline
CH & -0.521445 & 0.375512 & -1.389 & 0.166083 & 0.0830417 \tabularnewline
H & 0.513809 & 0.375348 & 1.369 & 0.172164 & 0.0860819 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268065&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]4.84357[/C][C]1.72036[/C][C]2.815[/C][C]0.00522732[/C][C]0.00261366[/C][/ROW]
[ROW][C]numeracy_tot[/C][C]0.0610439[/C][C]0.027364[/C][C]2.231[/C][C]0.0265092[/C][C]0.0132546[/C][/ROW]
[ROW][C]I1[/C][C]0.0745865[/C][C]0.0549343[/C][C]1.358[/C][C]0.175671[/C][C]0.0878357[/C][/ROW]
[ROW][C]I2[/C][C]-0.0620302[/C][C]0.0483463[/C][C]-1.283[/C][C]0.20057[/C][C]0.100285[/C][/ROW]
[ROW][C]I3[/C][C]0.00502049[/C][C]0.0411498[/C][C]0.122[/C][C]0.902985[/C][C]0.451493[/C][/ROW]
[ROW][C]E1[/C][C]-0.0574701[/C][C]0.0559826[/C][C]-1.027[/C][C]0.305535[/C][C]0.152767[/C][/ROW]
[ROW][C]E2[/C][C]-0.0142867[/C][C]0.039977[/C][C]-0.3574[/C][C]0.72109[/C][C]0.360545[/C][/ROW]
[ROW][C]E3[/C][C]-0.0243797[/C][C]0.0472352[/C][C]-0.5161[/C][C]0.606181[/C][C]0.30309[/C][/ROW]
[ROW][C]A[/C][C]0.0151911[/C][C]0.048301[/C][C]0.3145[/C][C]0.753376[/C][C]0.376688[/C][/ROW]
[ROW][C]LFM[/C][C]-0.000692744[/C][C]0.00405671[/C][C]-0.1708[/C][C]0.864535[/C][C]0.432268[/C][/ROW]
[ROW][C]B[/C][C]0.0172191[/C][C]0.00245926[/C][C]7.002[/C][C]1.97777e-11[/C][C]9.88886e-12[/C][/ROW]
[ROW][C]PRH[/C][C]-0.519251[/C][C]0.376094[/C][C]-1.381[/C][C]0.168522[/C][C]0.0842609[/C][/ROW]
[ROW][C]CH[/C][C]-0.521445[/C][C]0.375512[/C][C]-1.389[/C][C]0.166083[/C][C]0.0830417[/C][/ROW]
[ROW][C]H[/C][C]0.513809[/C][C]0.375348[/C][C]1.369[/C][C]0.172164[/C][C]0.0860819[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268065&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268065&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	4.84357	1.72036	2.815	0.00522732	0.00261366
numeracy_tot	0.0610439	0.027364	2.231	0.0265092	0.0132546
I1	0.0745865	0.0549343	1.358	0.175671	0.0878357
I2	-0.0620302	0.0483463	-1.283	0.20057	0.100285
I3	0.00502049	0.0411498	0.122	0.902985	0.451493
E1	-0.0574701	0.0559826	-1.027	0.305535	0.152767
E2	-0.0142867	0.039977	-0.3574	0.72109	0.360545
E3	-0.0243797	0.0472352	-0.5161	0.606181	0.30309
A	0.0151911	0.048301	0.3145	0.753376	0.376688
LFM	-0.000692744	0.00405671	-0.1708	0.864535	0.432268
B	0.0172191	0.00245926	7.002	1.97777e-11	9.88886e-12
PRH	-0.519251	0.376094	-1.381	0.168522	0.0842609
CH	-0.521445	0.375512	-1.389	0.166083	0.0830417
H	0.513809	0.375348	1.369	0.172164	0.0860819

Multiple Linear Regression - Regression Statistics
Multiple R	0.489215
R-squared	0.239332
Adjusted R-squared	0.202976
F-TEST (value)	6.5831
F-TEST (DF numerator)	13
F-TEST (DF denominator)	272
p-value	6.54945e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.28257
Sum Squared Residuals	1417.15

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.489215 \tabularnewline
R-squared & 0.239332 \tabularnewline
Adjusted R-squared & 0.202976 \tabularnewline
F-TEST (value) & 6.5831 \tabularnewline
F-TEST (DF numerator) & 13 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 6.54945e-11 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.28257 \tabularnewline
Sum Squared Residuals & 1417.15 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268065&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.489215[/C][/ROW]
[ROW][C]R-squared[/C][C]0.239332[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.202976[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]6.5831[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]13[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]6.54945e-11[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.28257[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1417.15[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268065&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268065&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R	0.489215
R-squared	0.239332
Adjusted R-squared	0.202976
F-TEST (value)	6.5831
F-TEST (DF numerator)	13
F-TEST (DF denominator)	272
p-value	6.54945e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.28257
Sum Squared Residuals	1417.15

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	5.78472	1.71528
2	2.5	5.17108	-2.67108
3	6	5.22008	0.779924
4	6.5	5.80965	0.690348
5	1	5.32298	-4.32298
6	1	5.37982	-4.37982
7	5.5	5.78613	-0.286128
8	8.5	5.39061	3.10939
9	6.5	6.37951	0.120486
10	4.5	4.77114	-0.271136
11	2	7.28385	-5.28385
12	5	5.58769	-0.587688
13	0.5	6.67774	-6.17774
14	5	4.6704	0.3296
15	5	5.48682	-0.486824
16	2.5	4.19042	-1.69042
17	5	5.05603	-0.0560319
18	5.5	5.95938	-0.459376
19	3.5	5.41042	-1.91042
20	3	5.89152	-2.89152
21	4	4.60168	-0.601682
22	0.5	4.66346	-4.16346
23	6.5	5.78819	0.711807
24	4.5	5.59883	-1.09883
25	7.5	4.75112	2.74888
26	5.5	5.83466	-0.334662
27	4	5.74389	-1.74389
28	7.5	6.22463	1.27537
29	7	5.5306	1.4694
30	4	5.10366	-1.10366
31	5.5	4.86869	0.631309
32	2.5	4.65391	-2.15391
33	5.5	6.42305	-0.923049
34	0.5	4.54233	-4.04233
35	3.5	5.68973	-2.18973
36	2.5	6.88733	-4.38733
37	4.5	5.66586	-1.16586
38	4.5	5.9241	-1.4241
39	4.5	4.72289	-0.222895
40	6	5.63613	0.363869
41	2.5	5.41627	-2.91627
42	5	6.62317	-1.62317
43	0	5.21893	-5.21893
44	5	6.75334	-1.75334
45	6.5	5.15793	1.34207
46	5	6.02558	-1.02558
47	6	4.98143	1.01857
48	4.5	5.95334	-1.45334
49	5.5	5.62041	-0.120414
50	1	4.717	-3.717
51	7.5	4.25988	3.24012
52	6	4.95368	1.04632
53	5	5.10645	-0.106449
54	1	5.76172	-4.76172
55	5	6.19229	-1.19229
56	6.5	5.35891	1.14109
57	7	6.43702	0.562981
58	4.5	7.04582	-2.54582
59	0	4.55414	-4.55414
60	8.5	5.27501	3.22499
61	3.5	4.25482	-0.754815
62	7.5	6.03219	1.46781
63	3.5	6.09304	-2.59304
64	6	4.94835	1.05165
65	1.5	4.72919	-3.22919
66	9	5.99883	3.00117
67	3.5	4.94412	-1.44412
68	3.5	5.41778	-1.91778
69	4	5.61733	-1.61733
70	6.5	5.72048	0.779522
71	7.5	5.24251	2.25749
72	6	4.86359	1.13641
73	5	6.33138	-1.33138
74	5.5	5.38699	0.113009
75	3.5	5.79573	-2.29573
76	7.5	5.32811	2.17189
77	1	5.36295	-4.36295
78	6.5	5.26725	1.23275
79	NA	NA	0.894188
80	6.5	5.6911	0.808903
81	6.5	6.19081	0.309187
82	7	8.00088	-1.00088
83	3.5	7.30415	-3.80415
84	1.5	2.59598	-1.09598
85	4	0.727582	3.27242
86	7.5	8.23376	-0.733763
87	4.5	9.15552	-4.65552
88	0	0.795237	-0.795237
89	3.5	3.51777	-0.0177708
90	5.5	5.34417	0.155834
91	5	5.02726	-0.0272568
92	4.5	6.72854	-2.22854
93	2.5	-0.46874	2.96874
94	7.5	5.65636	1.84364
95	7	12.2853	-5.28535
96	0	0.696314	-0.696314
97	4.5	7.06502	-2.56502
98	3	6.91309	-3.91309
99	1.5	2.4656	-0.9656
100	3.5	7.1281	-3.6281
101	2.5	2.34955	0.150451
102	5.5	2.88466	2.61534
103	8	11.4683	-3.46834
104	1	1.30137	-0.301373
105	5	5.47154	-0.471543
106	4.5	5.83128	-1.33128
107	3	4.59985	-1.59985
108	3	0.169889	2.83011
109	8	9.53324	-1.53324
110	2.5	0.42274	2.07726
111	7	11.5728	-4.5728
112	0	4.14699	-4.14699
113	1	2.02235	-1.02235
114	3.5	2.57406	0.925937
115	5.5	4.95786	0.542137
116	5.5	9.96331	-4.46331
117	0.5	-0.717594	1.21759
118	7.5	5.10433	2.39567
119	9	6.58313	2.41687
120	9.5	9.88158	-0.381579
121	8.5	6.5035	1.9965
122	7	10.7029	-3.70288
123	8	5.16995	2.83005
124	10	11.6349	-1.63488
125	7	3.74908	3.25092
126	8.5	8.81473	-0.31473
127	9	5.14073	3.85927
128	9.5	12.2786	-2.7786
129	4	4.17945	-0.179449
130	6	5.27285	0.727147
131	8	10.3084	-2.30838
132	5.5	3.74953	1.75047
133	9.5	8.53128	0.968719
134	7.5	6.67358	0.826415
135	7	7.88889	-0.888886
136	7.5	5.09	2.41
137	8	7.12523	0.874773
138	7	6.58782	0.412185
139	7	8.43858	-1.43858
140	6	2.98936	3.01064
141	10	13.7321	-3.7321
142	2.5	2.15661	0.343386
143	9	10.4657	-1.4657
144	8	7.47064	0.529362
145	6	1.74712	4.25288
146	8.5	7.2416	1.2584
147	6	4.34957	1.65043
148	9	7.26616	1.73384
149	8	6.72574	1.27426
150	8	6.61452	1.38548
151	9	9.46082	-0.46082
152	5.5	6.00747	-0.507468
153	5	4.34331	0.656693
154	7	10.6769	-3.67692
155	5.5	4.83913	0.660866
156	9	13.3957	-4.39566
157	2	0.445665	1.55433
158	8.5	7.12274	1.37726
159	9	9.06037	-0.0603677
160	8.5	6.18495	2.31505
161	9	9.14653	-0.14653
162	7.5	5.95168	1.54832
163	10	8.23375	1.76625
164	9	10.8912	-1.89118
165	7.5	8.16783	-0.667833
166	6	1.93022	4.06978
167	10.5	11.3587	-0.858745
168	8.5	7.94621	0.553795
169	8	4.37592	3.62408
170	10	6.51135	3.48865
171	10.5	9.30039	1.19961
172	6.5	5.2621	1.2379
173	9.5	5.84441	3.65559
174	8.5	9.08523	-0.585229
175	7.5	9.58598	-2.08598
176	5	4.80577	0.194232
177	8	4.49104	3.50896
178	10	8.9737	1.0263
179	7	7.27018	-0.270184
180	7.5	7.80528	-0.305276
181	7.5	4.34555	3.15445
182	9.5	10.4989	-0.998903
183	6	4.05208	1.94792
184	10	8.77785	1.22215
185	7	10.2777	-3.27774
186	3	4.05677	-1.05677
187	6	6.05356	-0.0535571
188	7	5.54915	1.45085
189	10	9.48686	0.51314
190	7	8.9066	-1.9066
191	3.5	2.88426	0.615741
192	8	4.10609	3.89391
193	10	10.3135	-0.313511
194	5.5	3.54323	1.95677
195	6	5.38725	0.612749
196	6.5	6.35031	0.149695
197	6.5	3.54982	2.95018
198	8.5	10.1592	-1.65917
199	4	0.499835	3.50017
200	9.5	7.94749	1.55251
201	8	8.11342	-0.113418
202	8.5	11.487	-2.98703
203	5.5	4.88916	0.610845
204	7	3.38209	3.61791
205	9	6.92016	2.07984
206	8	7.21892	0.781078
207	10	8.5807	1.4193
208	8	8.04294	-0.0429437
209	6	4.95939	1.04061
210	8	8.39639	-0.39639
211	5	1.90899	3.09101
212	9	11.1777	-2.17774
213	4.5	2.74089	1.75911
214	8.5	8.25648	0.243523
215	7	4.61379	2.38621
216	9.5	8.08045	1.41955
217	8.5	6.18131	2.31869
218	7.5	6.54181	0.958195
219	7.5	9.30969	-1.80969
220	5	6.21673	-1.21673
221	7	7.56493	-0.564929
222	8	8.7609	-0.7609
223	5.5	3.38186	2.11814
224	8.5	8.13439	0.365607
225	7.5	5.08993	2.41007
226	9.5	8.65841	0.841586
227	7	7.43626	-0.436259
228	8	6.71584	1.28416
229	8.5	10.814	-2.31402
230	3.5	3.7054	-0.205399
231	6.5	4.89097	1.60903
232	6.5	3.37125	3.12875
233	10.5	8.1797	2.3203
234	8.5	6.77823	1.72177
235	8	4.43044	3.56956
236	10	7.32598	2.67402
237	10	7.62083	2.37917
238	9.5	5.28512	4.21488
239	9	8.44762	0.552384
240	10	8.05693	1.94307
241	7.5	8.55875	-1.05875
242	4.5	4.49959	0.000412841
243	4.5	9.97437	-5.47437
244	0.5	-0.692945	1.19294
245	6.5	9.14886	-2.64886
246	4.5	5.26766	-0.76766
247	5.5	5.38115	0.118845
248	5	6.73625	-1.73625
249	6	8.3352	-2.3352
250	4	1.36858	2.63142
251	8	4.61474	3.38526
252	10.5	7.96137	2.53863
253	8.5	8.52621	-0.0262149
254	6.5	6.07932	0.420679
255	8	7.19126	0.808741
256	8.5	9.6557	-1.1557
257	5.5	6.16279	-0.662791
258	7	7.61508	-0.615078
259	5	6.48057	-1.48057
260	3.5	5.3372	-1.8372
261	5	3.39211	1.60789
262	9	6.54574	2.45426
263	8.5	10.1948	-1.69482
264	5	4.00283	0.997167
265	9.5	10.8741	-1.37412
266	3	8.88506	-5.88506
267	1.5	-0.304453	1.80445
268	6	10.8767	-4.87666
269	0.5	0.301703	0.198297
270	6.5	4.95456	1.54544
271	7.5	8.53027	-1.03027
272	4.5	2.27068	2.22932
273	8	6.75044	1.24956
274	9	8.39784	0.602157
275	7.5	7.07694	0.423055
276	8.5	6.14148	2.35852
277	7	3.61275	3.38725
278	9.5	8.15786	1.34214
279	6.5	1.59767	4.90233
280	9.5	8.35119	1.14881
281	6	3.95294	2.04706
282	8	6.71231	1.28769
283	9.5	7.70572	1.79428
284	8	6.60989	1.39011
285	8	5.5383	2.4617
286	9	10.0695	-1.06954
287	5	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.78472 & 1.71528 \tabularnewline
2 & 2.5 & 5.17108 & -2.67108 \tabularnewline
3 & 6 & 5.22008 & 0.779924 \tabularnewline
4 & 6.5 & 5.80965 & 0.690348 \tabularnewline
5 & 1 & 5.32298 & -4.32298 \tabularnewline
6 & 1 & 5.37982 & -4.37982 \tabularnewline
7 & 5.5 & 5.78613 & -0.286128 \tabularnewline
8 & 8.5 & 5.39061 & 3.10939 \tabularnewline
9 & 6.5 & 6.37951 & 0.120486 \tabularnewline
10 & 4.5 & 4.77114 & -0.271136 \tabularnewline
11 & 2 & 7.28385 & -5.28385 \tabularnewline
12 & 5 & 5.58769 & -0.587688 \tabularnewline
13 & 0.5 & 6.67774 & -6.17774 \tabularnewline
14 & 5 & 4.6704 & 0.3296 \tabularnewline
15 & 5 & 5.48682 & -0.486824 \tabularnewline
16 & 2.5 & 4.19042 & -1.69042 \tabularnewline
17 & 5 & 5.05603 & -0.0560319 \tabularnewline
18 & 5.5 & 5.95938 & -0.459376 \tabularnewline
19 & 3.5 & 5.41042 & -1.91042 \tabularnewline
20 & 3 & 5.89152 & -2.89152 \tabularnewline
21 & 4 & 4.60168 & -0.601682 \tabularnewline
22 & 0.5 & 4.66346 & -4.16346 \tabularnewline
23 & 6.5 & 5.78819 & 0.711807 \tabularnewline
24 & 4.5 & 5.59883 & -1.09883 \tabularnewline
25 & 7.5 & 4.75112 & 2.74888 \tabularnewline
26 & 5.5 & 5.83466 & -0.334662 \tabularnewline
27 & 4 & 5.74389 & -1.74389 \tabularnewline
28 & 7.5 & 6.22463 & 1.27537 \tabularnewline
29 & 7 & 5.5306 & 1.4694 \tabularnewline
30 & 4 & 5.10366 & -1.10366 \tabularnewline
31 & 5.5 & 4.86869 & 0.631309 \tabularnewline
32 & 2.5 & 4.65391 & -2.15391 \tabularnewline
33 & 5.5 & 6.42305 & -0.923049 \tabularnewline
34 & 0.5 & 4.54233 & -4.04233 \tabularnewline
35 & 3.5 & 5.68973 & -2.18973 \tabularnewline
36 & 2.5 & 6.88733 & -4.38733 \tabularnewline
37 & 4.5 & 5.66586 & -1.16586 \tabularnewline
38 & 4.5 & 5.9241 & -1.4241 \tabularnewline
39 & 4.5 & 4.72289 & -0.222895 \tabularnewline
40 & 6 & 5.63613 & 0.363869 \tabularnewline
41 & 2.5 & 5.41627 & -2.91627 \tabularnewline
42 & 5 & 6.62317 & -1.62317 \tabularnewline
43 & 0 & 5.21893 & -5.21893 \tabularnewline
44 & 5 & 6.75334 & -1.75334 \tabularnewline
45 & 6.5 & 5.15793 & 1.34207 \tabularnewline
46 & 5 & 6.02558 & -1.02558 \tabularnewline
47 & 6 & 4.98143 & 1.01857 \tabularnewline
48 & 4.5 & 5.95334 & -1.45334 \tabularnewline
49 & 5.5 & 5.62041 & -0.120414 \tabularnewline
50 & 1 & 4.717 & -3.717 \tabularnewline
51 & 7.5 & 4.25988 & 3.24012 \tabularnewline
52 & 6 & 4.95368 & 1.04632 \tabularnewline
53 & 5 & 5.10645 & -0.106449 \tabularnewline
54 & 1 & 5.76172 & -4.76172 \tabularnewline
55 & 5 & 6.19229 & -1.19229 \tabularnewline
56 & 6.5 & 5.35891 & 1.14109 \tabularnewline
57 & 7 & 6.43702 & 0.562981 \tabularnewline
58 & 4.5 & 7.04582 & -2.54582 \tabularnewline
59 & 0 & 4.55414 & -4.55414 \tabularnewline
60 & 8.5 & 5.27501 & 3.22499 \tabularnewline
61 & 3.5 & 4.25482 & -0.754815 \tabularnewline
62 & 7.5 & 6.03219 & 1.46781 \tabularnewline
63 & 3.5 & 6.09304 & -2.59304 \tabularnewline
64 & 6 & 4.94835 & 1.05165 \tabularnewline
65 & 1.5 & 4.72919 & -3.22919 \tabularnewline
66 & 9 & 5.99883 & 3.00117 \tabularnewline
67 & 3.5 & 4.94412 & -1.44412 \tabularnewline
68 & 3.5 & 5.41778 & -1.91778 \tabularnewline
69 & 4 & 5.61733 & -1.61733 \tabularnewline
70 & 6.5 & 5.72048 & 0.779522 \tabularnewline
71 & 7.5 & 5.24251 & 2.25749 \tabularnewline
72 & 6 & 4.86359 & 1.13641 \tabularnewline
73 & 5 & 6.33138 & -1.33138 \tabularnewline
74 & 5.5 & 5.38699 & 0.113009 \tabularnewline
75 & 3.5 & 5.79573 & -2.29573 \tabularnewline
76 & 7.5 & 5.32811 & 2.17189 \tabularnewline
77 & 1 & 5.36295 & -4.36295 \tabularnewline
78 & 6.5 & 5.26725 & 1.23275 \tabularnewline
79 & NA & NA & 0.894188 \tabularnewline
80 & 6.5 & 5.6911 & 0.808903 \tabularnewline
81 & 6.5 & 6.19081 & 0.309187 \tabularnewline
82 & 7 & 8.00088 & -1.00088 \tabularnewline
83 & 3.5 & 7.30415 & -3.80415 \tabularnewline
84 & 1.5 & 2.59598 & -1.09598 \tabularnewline
85 & 4 & 0.727582 & 3.27242 \tabularnewline
86 & 7.5 & 8.23376 & -0.733763 \tabularnewline
87 & 4.5 & 9.15552 & -4.65552 \tabularnewline
88 & 0 & 0.795237 & -0.795237 \tabularnewline
89 & 3.5 & 3.51777 & -0.0177708 \tabularnewline
90 & 5.5 & 5.34417 & 0.155834 \tabularnewline
91 & 5 & 5.02726 & -0.0272568 \tabularnewline
92 & 4.5 & 6.72854 & -2.22854 \tabularnewline
93 & 2.5 & -0.46874 & 2.96874 \tabularnewline
94 & 7.5 & 5.65636 & 1.84364 \tabularnewline
95 & 7 & 12.2853 & -5.28535 \tabularnewline
96 & 0 & 0.696314 & -0.696314 \tabularnewline
97 & 4.5 & 7.06502 & -2.56502 \tabularnewline
98 & 3 & 6.91309 & -3.91309 \tabularnewline
99 & 1.5 & 2.4656 & -0.9656 \tabularnewline
100 & 3.5 & 7.1281 & -3.6281 \tabularnewline
101 & 2.5 & 2.34955 & 0.150451 \tabularnewline
102 & 5.5 & 2.88466 & 2.61534 \tabularnewline
103 & 8 & 11.4683 & -3.46834 \tabularnewline
104 & 1 & 1.30137 & -0.301373 \tabularnewline
105 & 5 & 5.47154 & -0.471543 \tabularnewline
106 & 4.5 & 5.83128 & -1.33128 \tabularnewline
107 & 3 & 4.59985 & -1.59985 \tabularnewline
108 & 3 & 0.169889 & 2.83011 \tabularnewline
109 & 8 & 9.53324 & -1.53324 \tabularnewline
110 & 2.5 & 0.42274 & 2.07726 \tabularnewline
111 & 7 & 11.5728 & -4.5728 \tabularnewline
112 & 0 & 4.14699 & -4.14699 \tabularnewline
113 & 1 & 2.02235 & -1.02235 \tabularnewline
114 & 3.5 & 2.57406 & 0.925937 \tabularnewline
115 & 5.5 & 4.95786 & 0.542137 \tabularnewline
116 & 5.5 & 9.96331 & -4.46331 \tabularnewline
117 & 0.5 & -0.717594 & 1.21759 \tabularnewline
118 & 7.5 & 5.10433 & 2.39567 \tabularnewline
119 & 9 & 6.58313 & 2.41687 \tabularnewline
120 & 9.5 & 9.88158 & -0.381579 \tabularnewline
121 & 8.5 & 6.5035 & 1.9965 \tabularnewline
122 & 7 & 10.7029 & -3.70288 \tabularnewline
123 & 8 & 5.16995 & 2.83005 \tabularnewline
124 & 10 & 11.6349 & -1.63488 \tabularnewline
125 & 7 & 3.74908 & 3.25092 \tabularnewline
126 & 8.5 & 8.81473 & -0.31473 \tabularnewline
127 & 9 & 5.14073 & 3.85927 \tabularnewline
128 & 9.5 & 12.2786 & -2.7786 \tabularnewline
129 & 4 & 4.17945 & -0.179449 \tabularnewline
130 & 6 & 5.27285 & 0.727147 \tabularnewline
131 & 8 & 10.3084 & -2.30838 \tabularnewline
132 & 5.5 & 3.74953 & 1.75047 \tabularnewline
133 & 9.5 & 8.53128 & 0.968719 \tabularnewline
134 & 7.5 & 6.67358 & 0.826415 \tabularnewline
135 & 7 & 7.88889 & -0.888886 \tabularnewline
136 & 7.5 & 5.09 & 2.41 \tabularnewline
137 & 8 & 7.12523 & 0.874773 \tabularnewline
138 & 7 & 6.58782 & 0.412185 \tabularnewline
139 & 7 & 8.43858 & -1.43858 \tabularnewline
140 & 6 & 2.98936 & 3.01064 \tabularnewline
141 & 10 & 13.7321 & -3.7321 \tabularnewline
142 & 2.5 & 2.15661 & 0.343386 \tabularnewline
143 & 9 & 10.4657 & -1.4657 \tabularnewline
144 & 8 & 7.47064 & 0.529362 \tabularnewline
145 & 6 & 1.74712 & 4.25288 \tabularnewline
146 & 8.5 & 7.2416 & 1.2584 \tabularnewline
147 & 6 & 4.34957 & 1.65043 \tabularnewline
148 & 9 & 7.26616 & 1.73384 \tabularnewline
149 & 8 & 6.72574 & 1.27426 \tabularnewline
150 & 8 & 6.61452 & 1.38548 \tabularnewline
151 & 9 & 9.46082 & -0.46082 \tabularnewline
152 & 5.5 & 6.00747 & -0.507468 \tabularnewline
153 & 5 & 4.34331 & 0.656693 \tabularnewline
154 & 7 & 10.6769 & -3.67692 \tabularnewline
155 & 5.5 & 4.83913 & 0.660866 \tabularnewline
156 & 9 & 13.3957 & -4.39566 \tabularnewline
157 & 2 & 0.445665 & 1.55433 \tabularnewline
158 & 8.5 & 7.12274 & 1.37726 \tabularnewline
159 & 9 & 9.06037 & -0.0603677 \tabularnewline
160 & 8.5 & 6.18495 & 2.31505 \tabularnewline
161 & 9 & 9.14653 & -0.14653 \tabularnewline
162 & 7.5 & 5.95168 & 1.54832 \tabularnewline
163 & 10 & 8.23375 & 1.76625 \tabularnewline
164 & 9 & 10.8912 & -1.89118 \tabularnewline
165 & 7.5 & 8.16783 & -0.667833 \tabularnewline
166 & 6 & 1.93022 & 4.06978 \tabularnewline
167 & 10.5 & 11.3587 & -0.858745 \tabularnewline
168 & 8.5 & 7.94621 & 0.553795 \tabularnewline
169 & 8 & 4.37592 & 3.62408 \tabularnewline
170 & 10 & 6.51135 & 3.48865 \tabularnewline
171 & 10.5 & 9.30039 & 1.19961 \tabularnewline
172 & 6.5 & 5.2621 & 1.2379 \tabularnewline
173 & 9.5 & 5.84441 & 3.65559 \tabularnewline
174 & 8.5 & 9.08523 & -0.585229 \tabularnewline
175 & 7.5 & 9.58598 & -2.08598 \tabularnewline
176 & 5 & 4.80577 & 0.194232 \tabularnewline
177 & 8 & 4.49104 & 3.50896 \tabularnewline
178 & 10 & 8.9737 & 1.0263 \tabularnewline
179 & 7 & 7.27018 & -0.270184 \tabularnewline
180 & 7.5 & 7.80528 & -0.305276 \tabularnewline
181 & 7.5 & 4.34555 & 3.15445 \tabularnewline
182 & 9.5 & 10.4989 & -0.998903 \tabularnewline
183 & 6 & 4.05208 & 1.94792 \tabularnewline
184 & 10 & 8.77785 & 1.22215 \tabularnewline
185 & 7 & 10.2777 & -3.27774 \tabularnewline
186 & 3 & 4.05677 & -1.05677 \tabularnewline
187 & 6 & 6.05356 & -0.0535571 \tabularnewline
188 & 7 & 5.54915 & 1.45085 \tabularnewline
189 & 10 & 9.48686 & 0.51314 \tabularnewline
190 & 7 & 8.9066 & -1.9066 \tabularnewline
191 & 3.5 & 2.88426 & 0.615741 \tabularnewline
192 & 8 & 4.10609 & 3.89391 \tabularnewline
193 & 10 & 10.3135 & -0.313511 \tabularnewline
194 & 5.5 & 3.54323 & 1.95677 \tabularnewline
195 & 6 & 5.38725 & 0.612749 \tabularnewline
196 & 6.5 & 6.35031 & 0.149695 \tabularnewline
197 & 6.5 & 3.54982 & 2.95018 \tabularnewline
198 & 8.5 & 10.1592 & -1.65917 \tabularnewline
199 & 4 & 0.499835 & 3.50017 \tabularnewline
200 & 9.5 & 7.94749 & 1.55251 \tabularnewline
201 & 8 & 8.11342 & -0.113418 \tabularnewline
202 & 8.5 & 11.487 & -2.98703 \tabularnewline
203 & 5.5 & 4.88916 & 0.610845 \tabularnewline
204 & 7 & 3.38209 & 3.61791 \tabularnewline
205 & 9 & 6.92016 & 2.07984 \tabularnewline
206 & 8 & 7.21892 & 0.781078 \tabularnewline
207 & 10 & 8.5807 & 1.4193 \tabularnewline
208 & 8 & 8.04294 & -0.0429437 \tabularnewline
209 & 6 & 4.95939 & 1.04061 \tabularnewline
210 & 8 & 8.39639 & -0.39639 \tabularnewline
211 & 5 & 1.90899 & 3.09101 \tabularnewline
212 & 9 & 11.1777 & -2.17774 \tabularnewline
213 & 4.5 & 2.74089 & 1.75911 \tabularnewline
214 & 8.5 & 8.25648 & 0.243523 \tabularnewline
215 & 7 & 4.61379 & 2.38621 \tabularnewline
216 & 9.5 & 8.08045 & 1.41955 \tabularnewline
217 & 8.5 & 6.18131 & 2.31869 \tabularnewline
218 & 7.5 & 6.54181 & 0.958195 \tabularnewline
219 & 7.5 & 9.30969 & -1.80969 \tabularnewline
220 & 5 & 6.21673 & -1.21673 \tabularnewline
221 & 7 & 7.56493 & -0.564929 \tabularnewline
222 & 8 & 8.7609 & -0.7609 \tabularnewline
223 & 5.5 & 3.38186 & 2.11814 \tabularnewline
224 & 8.5 & 8.13439 & 0.365607 \tabularnewline
225 & 7.5 & 5.08993 & 2.41007 \tabularnewline
226 & 9.5 & 8.65841 & 0.841586 \tabularnewline
227 & 7 & 7.43626 & -0.436259 \tabularnewline
228 & 8 & 6.71584 & 1.28416 \tabularnewline
229 & 8.5 & 10.814 & -2.31402 \tabularnewline
230 & 3.5 & 3.7054 & -0.205399 \tabularnewline
231 & 6.5 & 4.89097 & 1.60903 \tabularnewline
232 & 6.5 & 3.37125 & 3.12875 \tabularnewline
233 & 10.5 & 8.1797 & 2.3203 \tabularnewline
234 & 8.5 & 6.77823 & 1.72177 \tabularnewline
235 & 8 & 4.43044 & 3.56956 \tabularnewline
236 & 10 & 7.32598 & 2.67402 \tabularnewline
237 & 10 & 7.62083 & 2.37917 \tabularnewline
238 & 9.5 & 5.28512 & 4.21488 \tabularnewline
239 & 9 & 8.44762 & 0.552384 \tabularnewline
240 & 10 & 8.05693 & 1.94307 \tabularnewline
241 & 7.5 & 8.55875 & -1.05875 \tabularnewline
242 & 4.5 & 4.49959 & 0.000412841 \tabularnewline
243 & 4.5 & 9.97437 & -5.47437 \tabularnewline
244 & 0.5 & -0.692945 & 1.19294 \tabularnewline
245 & 6.5 & 9.14886 & -2.64886 \tabularnewline
246 & 4.5 & 5.26766 & -0.76766 \tabularnewline
247 & 5.5 & 5.38115 & 0.118845 \tabularnewline
248 & 5 & 6.73625 & -1.73625 \tabularnewline
249 & 6 & 8.3352 & -2.3352 \tabularnewline
250 & 4 & 1.36858 & 2.63142 \tabularnewline
251 & 8 & 4.61474 & 3.38526 \tabularnewline
252 & 10.5 & 7.96137 & 2.53863 \tabularnewline
253 & 8.5 & 8.52621 & -0.0262149 \tabularnewline
254 & 6.5 & 6.07932 & 0.420679 \tabularnewline
255 & 8 & 7.19126 & 0.808741 \tabularnewline
256 & 8.5 & 9.6557 & -1.1557 \tabularnewline
257 & 5.5 & 6.16279 & -0.662791 \tabularnewline
258 & 7 & 7.61508 & -0.615078 \tabularnewline
259 & 5 & 6.48057 & -1.48057 \tabularnewline
260 & 3.5 & 5.3372 & -1.8372 \tabularnewline
261 & 5 & 3.39211 & 1.60789 \tabularnewline
262 & 9 & 6.54574 & 2.45426 \tabularnewline
263 & 8.5 & 10.1948 & -1.69482 \tabularnewline
264 & 5 & 4.00283 & 0.997167 \tabularnewline
265 & 9.5 & 10.8741 & -1.37412 \tabularnewline
266 & 3 & 8.88506 & -5.88506 \tabularnewline
267 & 1.5 & -0.304453 & 1.80445 \tabularnewline
268 & 6 & 10.8767 & -4.87666 \tabularnewline
269 & 0.5 & 0.301703 & 0.198297 \tabularnewline
270 & 6.5 & 4.95456 & 1.54544 \tabularnewline
271 & 7.5 & 8.53027 & -1.03027 \tabularnewline
272 & 4.5 & 2.27068 & 2.22932 \tabularnewline
273 & 8 & 6.75044 & 1.24956 \tabularnewline
274 & 9 & 8.39784 & 0.602157 \tabularnewline
275 & 7.5 & 7.07694 & 0.423055 \tabularnewline
276 & 8.5 & 6.14148 & 2.35852 \tabularnewline
277 & 7 & 3.61275 & 3.38725 \tabularnewline
278 & 9.5 & 8.15786 & 1.34214 \tabularnewline
279 & 6.5 & 1.59767 & 4.90233 \tabularnewline
280 & 9.5 & 8.35119 & 1.14881 \tabularnewline
281 & 6 & 3.95294 & 2.04706 \tabularnewline
282 & 8 & 6.71231 & 1.28769 \tabularnewline
283 & 9.5 & 7.70572 & 1.79428 \tabularnewline
284 & 8 & 6.60989 & 1.39011 \tabularnewline
285 & 8 & 5.5383 & 2.4617 \tabularnewline
286 & 9 & 10.0695 & -1.06954 \tabularnewline
287 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268065&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]5.78472[/C][C]1.71528[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]5.17108[/C][C]-2.67108[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]5.22008[/C][C]0.779924[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]5.80965[/C][C]0.690348[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.32298[/C][C]-4.32298[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]5.37982[/C][C]-4.37982[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]5.78613[/C][C]-0.286128[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]5.39061[/C][C]3.10939[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]6.37951[/C][C]0.120486[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]4.77114[/C][C]-0.271136[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]7.28385[/C][C]-5.28385[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]5.58769[/C][C]-0.587688[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]6.67774[/C][C]-6.17774[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]4.6704[/C][C]0.3296[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]5.48682[/C][C]-0.486824[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]4.19042[/C][C]-1.69042[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]5.05603[/C][C]-0.0560319[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]5.95938[/C][C]-0.459376[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]5.41042[/C][C]-1.91042[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]5.89152[/C][C]-2.89152[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]4.60168[/C][C]-0.601682[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]4.66346[/C][C]-4.16346[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]5.78819[/C][C]0.711807[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]5.59883[/C][C]-1.09883[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]4.75112[/C][C]2.74888[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]5.83466[/C][C]-0.334662[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]5.74389[/C][C]-1.74389[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]6.22463[/C][C]1.27537[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]5.5306[/C][C]1.4694[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]5.10366[/C][C]-1.10366[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]4.86869[/C][C]0.631309[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]4.65391[/C][C]-2.15391[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]6.42305[/C][C]-0.923049[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]4.54233[/C][C]-4.04233[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]5.68973[/C][C]-2.18973[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]6.88733[/C][C]-4.38733[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.66586[/C][C]-1.16586[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]5.9241[/C][C]-1.4241[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]4.72289[/C][C]-0.222895[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.63613[/C][C]0.363869[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]5.41627[/C][C]-2.91627[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.62317[/C][C]-1.62317[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]5.21893[/C][C]-5.21893[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.75334[/C][C]-1.75334[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]5.15793[/C][C]1.34207[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]6.02558[/C][C]-1.02558[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]4.98143[/C][C]1.01857[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]5.95334[/C][C]-1.45334[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]5.62041[/C][C]-0.120414[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]4.717[/C][C]-3.717[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]4.25988[/C][C]3.24012[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]4.95368[/C][C]1.04632[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.10645[/C][C]-0.106449[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]5.76172[/C][C]-4.76172[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]6.19229[/C][C]-1.19229[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]5.35891[/C][C]1.14109[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]6.43702[/C][C]0.562981[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]7.04582[/C][C]-2.54582[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]4.55414[/C][C]-4.55414[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]5.27501[/C][C]3.22499[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.25482[/C][C]-0.754815[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]6.03219[/C][C]1.46781[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]6.09304[/C][C]-2.59304[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]4.94835[/C][C]1.05165[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]4.72919[/C][C]-3.22919[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]5.99883[/C][C]3.00117[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]4.94412[/C][C]-1.44412[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]5.41778[/C][C]-1.91778[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]5.61733[/C][C]-1.61733[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]5.72048[/C][C]0.779522[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]5.24251[/C][C]2.25749[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]4.86359[/C][C]1.13641[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]6.33138[/C][C]-1.33138[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]5.38699[/C][C]0.113009[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]5.79573[/C][C]-2.29573[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]5.32811[/C][C]2.17189[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]5.36295[/C][C]-4.36295[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.26725[/C][C]1.23275[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]0.894188[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]5.6911[/C][C]0.808903[/C][/ROW]
[ROW][C]81[/C][C]6.5[/C][C]6.19081[/C][C]0.309187[/C][/ROW]
[ROW][C]82[/C][C]7[/C][C]8.00088[/C][C]-1.00088[/C][/ROW]
[ROW][C]83[/C][C]3.5[/C][C]7.30415[/C][C]-3.80415[/C][/ROW]
[ROW][C]84[/C][C]1.5[/C][C]2.59598[/C][C]-1.09598[/C][/ROW]
[ROW][C]85[/C][C]4[/C][C]0.727582[/C][C]3.27242[/C][/ROW]
[ROW][C]86[/C][C]7.5[/C][C]8.23376[/C][C]-0.733763[/C][/ROW]
[ROW][C]87[/C][C]4.5[/C][C]9.15552[/C][C]-4.65552[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]0.795237[/C][C]-0.795237[/C][/ROW]
[ROW][C]89[/C][C]3.5[/C][C]3.51777[/C][C]-0.0177708[/C][/ROW]
[ROW][C]90[/C][C]5.5[/C][C]5.34417[/C][C]0.155834[/C][/ROW]
[ROW][C]91[/C][C]5[/C][C]5.02726[/C][C]-0.0272568[/C][/ROW]
[ROW][C]92[/C][C]4.5[/C][C]6.72854[/C][C]-2.22854[/C][/ROW]
[ROW][C]93[/C][C]2.5[/C][C]-0.46874[/C][C]2.96874[/C][/ROW]
[ROW][C]94[/C][C]7.5[/C][C]5.65636[/C][C]1.84364[/C][/ROW]
[ROW][C]95[/C][C]7[/C][C]12.2853[/C][C]-5.28535[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.696314[/C][C]-0.696314[/C][/ROW]
[ROW][C]97[/C][C]4.5[/C][C]7.06502[/C][C]-2.56502[/C][/ROW]
[ROW][C]98[/C][C]3[/C][C]6.91309[/C][C]-3.91309[/C][/ROW]
[ROW][C]99[/C][C]1.5[/C][C]2.4656[/C][C]-0.9656[/C][/ROW]
[ROW][C]100[/C][C]3.5[/C][C]7.1281[/C][C]-3.6281[/C][/ROW]
[ROW][C]101[/C][C]2.5[/C][C]2.34955[/C][C]0.150451[/C][/ROW]
[ROW][C]102[/C][C]5.5[/C][C]2.88466[/C][C]2.61534[/C][/ROW]
[ROW][C]103[/C][C]8[/C][C]11.4683[/C][C]-3.46834[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]1.30137[/C][C]-0.301373[/C][/ROW]
[ROW][C]105[/C][C]5[/C][C]5.47154[/C][C]-0.471543[/C][/ROW]
[ROW][C]106[/C][C]4.5[/C][C]5.83128[/C][C]-1.33128[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]4.59985[/C][C]-1.59985[/C][/ROW]
[ROW][C]108[/C][C]3[/C][C]0.169889[/C][C]2.83011[/C][/ROW]
[ROW][C]109[/C][C]8[/C][C]9.53324[/C][C]-1.53324[/C][/ROW]
[ROW][C]110[/C][C]2.5[/C][C]0.42274[/C][C]2.07726[/C][/ROW]
[ROW][C]111[/C][C]7[/C][C]11.5728[/C][C]-4.5728[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]4.14699[/C][C]-4.14699[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]2.02235[/C][C]-1.02235[/C][/ROW]
[ROW][C]114[/C][C]3.5[/C][C]2.57406[/C][C]0.925937[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]4.95786[/C][C]0.542137[/C][/ROW]
[ROW][C]116[/C][C]5.5[/C][C]9.96331[/C][C]-4.46331[/C][/ROW]
[ROW][C]117[/C][C]0.5[/C][C]-0.717594[/C][C]1.21759[/C][/ROW]
[ROW][C]118[/C][C]7.5[/C][C]5.10433[/C][C]2.39567[/C][/ROW]
[ROW][C]119[/C][C]9[/C][C]6.58313[/C][C]2.41687[/C][/ROW]
[ROW][C]120[/C][C]9.5[/C][C]9.88158[/C][C]-0.381579[/C][/ROW]
[ROW][C]121[/C][C]8.5[/C][C]6.5035[/C][C]1.9965[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]10.7029[/C][C]-3.70288[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]5.16995[/C][C]2.83005[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]11.6349[/C][C]-1.63488[/C][/ROW]
[ROW][C]125[/C][C]7[/C][C]3.74908[/C][C]3.25092[/C][/ROW]
[ROW][C]126[/C][C]8.5[/C][C]8.81473[/C][C]-0.31473[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]5.14073[/C][C]3.85927[/C][/ROW]
[ROW][C]128[/C][C]9.5[/C][C]12.2786[/C][C]-2.7786[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]4.17945[/C][C]-0.179449[/C][/ROW]
[ROW][C]130[/C][C]6[/C][C]5.27285[/C][C]0.727147[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]10.3084[/C][C]-2.30838[/C][/ROW]
[ROW][C]132[/C][C]5.5[/C][C]3.74953[/C][C]1.75047[/C][/ROW]
[ROW][C]133[/C][C]9.5[/C][C]8.53128[/C][C]0.968719[/C][/ROW]
[ROW][C]134[/C][C]7.5[/C][C]6.67358[/C][C]0.826415[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]7.88889[/C][C]-0.888886[/C][/ROW]
[ROW][C]136[/C][C]7.5[/C][C]5.09[/C][C]2.41[/C][/ROW]
[ROW][C]137[/C][C]8[/C][C]7.12523[/C][C]0.874773[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]6.58782[/C][C]0.412185[/C][/ROW]
[ROW][C]139[/C][C]7[/C][C]8.43858[/C][C]-1.43858[/C][/ROW]
[ROW][C]140[/C][C]6[/C][C]2.98936[/C][C]3.01064[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.7321[/C][C]-3.7321[/C][/ROW]
[ROW][C]142[/C][C]2.5[/C][C]2.15661[/C][C]0.343386[/C][/ROW]
[ROW][C]143[/C][C]9[/C][C]10.4657[/C][C]-1.4657[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]7.47064[/C][C]0.529362[/C][/ROW]
[ROW][C]145[/C][C]6[/C][C]1.74712[/C][C]4.25288[/C][/ROW]
[ROW][C]146[/C][C]8.5[/C][C]7.2416[/C][C]1.2584[/C][/ROW]
[ROW][C]147[/C][C]6[/C][C]4.34957[/C][C]1.65043[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]7.26616[/C][C]1.73384[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]6.72574[/C][C]1.27426[/C][/ROW]
[ROW][C]150[/C][C]8[/C][C]6.61452[/C][C]1.38548[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]9.46082[/C][C]-0.46082[/C][/ROW]
[ROW][C]152[/C][C]5.5[/C][C]6.00747[/C][C]-0.507468[/C][/ROW]
[ROW][C]153[/C][C]5[/C][C]4.34331[/C][C]0.656693[/C][/ROW]
[ROW][C]154[/C][C]7[/C][C]10.6769[/C][C]-3.67692[/C][/ROW]
[ROW][C]155[/C][C]5.5[/C][C]4.83913[/C][C]0.660866[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]13.3957[/C][C]-4.39566[/C][/ROW]
[ROW][C]157[/C][C]2[/C][C]0.445665[/C][C]1.55433[/C][/ROW]
[ROW][C]158[/C][C]8.5[/C][C]7.12274[/C][C]1.37726[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]9.06037[/C][C]-0.0603677[/C][/ROW]
[ROW][C]160[/C][C]8.5[/C][C]6.18495[/C][C]2.31505[/C][/ROW]
[ROW][C]161[/C][C]9[/C][C]9.14653[/C][C]-0.14653[/C][/ROW]
[ROW][C]162[/C][C]7.5[/C][C]5.95168[/C][C]1.54832[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]8.23375[/C][C]1.76625[/C][/ROW]
[ROW][C]164[/C][C]9[/C][C]10.8912[/C][C]-1.89118[/C][/ROW]
[ROW][C]165[/C][C]7.5[/C][C]8.16783[/C][C]-0.667833[/C][/ROW]
[ROW][C]166[/C][C]6[/C][C]1.93022[/C][C]4.06978[/C][/ROW]
[ROW][C]167[/C][C]10.5[/C][C]11.3587[/C][C]-0.858745[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]7.94621[/C][C]0.553795[/C][/ROW]
[ROW][C]169[/C][C]8[/C][C]4.37592[/C][C]3.62408[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]6.51135[/C][C]3.48865[/C][/ROW]
[ROW][C]171[/C][C]10.5[/C][C]9.30039[/C][C]1.19961[/C][/ROW]
[ROW][C]172[/C][C]6.5[/C][C]5.2621[/C][C]1.2379[/C][/ROW]
[ROW][C]173[/C][C]9.5[/C][C]5.84441[/C][C]3.65559[/C][/ROW]
[ROW][C]174[/C][C]8.5[/C][C]9.08523[/C][C]-0.585229[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]9.58598[/C][C]-2.08598[/C][/ROW]
[ROW][C]176[/C][C]5[/C][C]4.80577[/C][C]0.194232[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]4.49104[/C][C]3.50896[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.9737[/C][C]1.0263[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]7.27018[/C][C]-0.270184[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]7.80528[/C][C]-0.305276[/C][/ROW]
[ROW][C]181[/C][C]7.5[/C][C]4.34555[/C][C]3.15445[/C][/ROW]
[ROW][C]182[/C][C]9.5[/C][C]10.4989[/C][C]-0.998903[/C][/ROW]
[ROW][C]183[/C][C]6[/C][C]4.05208[/C][C]1.94792[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]8.77785[/C][C]1.22215[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]10.2777[/C][C]-3.27774[/C][/ROW]
[ROW][C]186[/C][C]3[/C][C]4.05677[/C][C]-1.05677[/C][/ROW]
[ROW][C]187[/C][C]6[/C][C]6.05356[/C][C]-0.0535571[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]5.54915[/C][C]1.45085[/C][/ROW]
[ROW][C]189[/C][C]10[/C][C]9.48686[/C][C]0.51314[/C][/ROW]
[ROW][C]190[/C][C]7[/C][C]8.9066[/C][C]-1.9066[/C][/ROW]
[ROW][C]191[/C][C]3.5[/C][C]2.88426[/C][C]0.615741[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]4.10609[/C][C]3.89391[/C][/ROW]
[ROW][C]193[/C][C]10[/C][C]10.3135[/C][C]-0.313511[/C][/ROW]
[ROW][C]194[/C][C]5.5[/C][C]3.54323[/C][C]1.95677[/C][/ROW]
[ROW][C]195[/C][C]6[/C][C]5.38725[/C][C]0.612749[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]6.35031[/C][C]0.149695[/C][/ROW]
[ROW][C]197[/C][C]6.5[/C][C]3.54982[/C][C]2.95018[/C][/ROW]
[ROW][C]198[/C][C]8.5[/C][C]10.1592[/C][C]-1.65917[/C][/ROW]
[ROW][C]199[/C][C]4[/C][C]0.499835[/C][C]3.50017[/C][/ROW]
[ROW][C]200[/C][C]9.5[/C][C]7.94749[/C][C]1.55251[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]8.11342[/C][C]-0.113418[/C][/ROW]
[ROW][C]202[/C][C]8.5[/C][C]11.487[/C][C]-2.98703[/C][/ROW]
[ROW][C]203[/C][C]5.5[/C][C]4.88916[/C][C]0.610845[/C][/ROW]
[ROW][C]204[/C][C]7[/C][C]3.38209[/C][C]3.61791[/C][/ROW]
[ROW][C]205[/C][C]9[/C][C]6.92016[/C][C]2.07984[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]7.21892[/C][C]0.781078[/C][/ROW]
[ROW][C]207[/C][C]10[/C][C]8.5807[/C][C]1.4193[/C][/ROW]
[ROW][C]208[/C][C]8[/C][C]8.04294[/C][C]-0.0429437[/C][/ROW]
[ROW][C]209[/C][C]6[/C][C]4.95939[/C][C]1.04061[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]8.39639[/C][C]-0.39639[/C][/ROW]
[ROW][C]211[/C][C]5[/C][C]1.90899[/C][C]3.09101[/C][/ROW]
[ROW][C]212[/C][C]9[/C][C]11.1777[/C][C]-2.17774[/C][/ROW]
[ROW][C]213[/C][C]4.5[/C][C]2.74089[/C][C]1.75911[/C][/ROW]
[ROW][C]214[/C][C]8.5[/C][C]8.25648[/C][C]0.243523[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]4.61379[/C][C]2.38621[/C][/ROW]
[ROW][C]216[/C][C]9.5[/C][C]8.08045[/C][C]1.41955[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]6.18131[/C][C]2.31869[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]6.54181[/C][C]0.958195[/C][/ROW]
[ROW][C]219[/C][C]7.5[/C][C]9.30969[/C][C]-1.80969[/C][/ROW]
[ROW][C]220[/C][C]5[/C][C]6.21673[/C][C]-1.21673[/C][/ROW]
[ROW][C]221[/C][C]7[/C][C]7.56493[/C][C]-0.564929[/C][/ROW]
[ROW][C]222[/C][C]8[/C][C]8.7609[/C][C]-0.7609[/C][/ROW]
[ROW][C]223[/C][C]5.5[/C][C]3.38186[/C][C]2.11814[/C][/ROW]
[ROW][C]224[/C][C]8.5[/C][C]8.13439[/C][C]0.365607[/C][/ROW]
[ROW][C]225[/C][C]7.5[/C][C]5.08993[/C][C]2.41007[/C][/ROW]
[ROW][C]226[/C][C]9.5[/C][C]8.65841[/C][C]0.841586[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]7.43626[/C][C]-0.436259[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]6.71584[/C][C]1.28416[/C][/ROW]
[ROW][C]229[/C][C]8.5[/C][C]10.814[/C][C]-2.31402[/C][/ROW]
[ROW][C]230[/C][C]3.5[/C][C]3.7054[/C][C]-0.205399[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]4.89097[/C][C]1.60903[/C][/ROW]
[ROW][C]232[/C][C]6.5[/C][C]3.37125[/C][C]3.12875[/C][/ROW]
[ROW][C]233[/C][C]10.5[/C][C]8.1797[/C][C]2.3203[/C][/ROW]
[ROW][C]234[/C][C]8.5[/C][C]6.77823[/C][C]1.72177[/C][/ROW]
[ROW][C]235[/C][C]8[/C][C]4.43044[/C][C]3.56956[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]7.32598[/C][C]2.67402[/C][/ROW]
[ROW][C]237[/C][C]10[/C][C]7.62083[/C][C]2.37917[/C][/ROW]
[ROW][C]238[/C][C]9.5[/C][C]5.28512[/C][C]4.21488[/C][/ROW]
[ROW][C]239[/C][C]9[/C][C]8.44762[/C][C]0.552384[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]8.05693[/C][C]1.94307[/C][/ROW]
[ROW][C]241[/C][C]7.5[/C][C]8.55875[/C][C]-1.05875[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]4.49959[/C][C]0.000412841[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]9.97437[/C][C]-5.47437[/C][/ROW]
[ROW][C]244[/C][C]0.5[/C][C]-0.692945[/C][C]1.19294[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]9.14886[/C][C]-2.64886[/C][/ROW]
[ROW][C]246[/C][C]4.5[/C][C]5.26766[/C][C]-0.76766[/C][/ROW]
[ROW][C]247[/C][C]5.5[/C][C]5.38115[/C][C]0.118845[/C][/ROW]
[ROW][C]248[/C][C]5[/C][C]6.73625[/C][C]-1.73625[/C][/ROW]
[ROW][C]249[/C][C]6[/C][C]8.3352[/C][C]-2.3352[/C][/ROW]
[ROW][C]250[/C][C]4[/C][C]1.36858[/C][C]2.63142[/C][/ROW]
[ROW][C]251[/C][C]8[/C][C]4.61474[/C][C]3.38526[/C][/ROW]
[ROW][C]252[/C][C]10.5[/C][C]7.96137[/C][C]2.53863[/C][/ROW]
[ROW][C]253[/C][C]8.5[/C][C]8.52621[/C][C]-0.0262149[/C][/ROW]
[ROW][C]254[/C][C]6.5[/C][C]6.07932[/C][C]0.420679[/C][/ROW]
[ROW][C]255[/C][C]8[/C][C]7.19126[/C][C]0.808741[/C][/ROW]
[ROW][C]256[/C][C]8.5[/C][C]9.6557[/C][C]-1.1557[/C][/ROW]
[ROW][C]257[/C][C]5.5[/C][C]6.16279[/C][C]-0.662791[/C][/ROW]
[ROW][C]258[/C][C]7[/C][C]7.61508[/C][C]-0.615078[/C][/ROW]
[ROW][C]259[/C][C]5[/C][C]6.48057[/C][C]-1.48057[/C][/ROW]
[ROW][C]260[/C][C]3.5[/C][C]5.3372[/C][C]-1.8372[/C][/ROW]
[ROW][C]261[/C][C]5[/C][C]3.39211[/C][C]1.60789[/C][/ROW]
[ROW][C]262[/C][C]9[/C][C]6.54574[/C][C]2.45426[/C][/ROW]
[ROW][C]263[/C][C]8.5[/C][C]10.1948[/C][C]-1.69482[/C][/ROW]
[ROW][C]264[/C][C]5[/C][C]4.00283[/C][C]0.997167[/C][/ROW]
[ROW][C]265[/C][C]9.5[/C][C]10.8741[/C][C]-1.37412[/C][/ROW]
[ROW][C]266[/C][C]3[/C][C]8.88506[/C][C]-5.88506[/C][/ROW]
[ROW][C]267[/C][C]1.5[/C][C]-0.304453[/C][C]1.80445[/C][/ROW]
[ROW][C]268[/C][C]6[/C][C]10.8767[/C][C]-4.87666[/C][/ROW]
[ROW][C]269[/C][C]0.5[/C][C]0.301703[/C][C]0.198297[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]4.95456[/C][C]1.54544[/C][/ROW]
[ROW][C]271[/C][C]7.5[/C][C]8.53027[/C][C]-1.03027[/C][/ROW]
[ROW][C]272[/C][C]4.5[/C][C]2.27068[/C][C]2.22932[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]6.75044[/C][C]1.24956[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]8.39784[/C][C]0.602157[/C][/ROW]
[ROW][C]275[/C][C]7.5[/C][C]7.07694[/C][C]0.423055[/C][/ROW]
[ROW][C]276[/C][C]8.5[/C][C]6.14148[/C][C]2.35852[/C][/ROW]
[ROW][C]277[/C][C]7[/C][C]3.61275[/C][C]3.38725[/C][/ROW]
[ROW][C]278[/C][C]9.5[/C][C]8.15786[/C][C]1.34214[/C][/ROW]
[ROW][C]279[/C][C]6.5[/C][C]1.59767[/C][C]4.90233[/C][/ROW]
[ROW][C]280[/C][C]9.5[/C][C]8.35119[/C][C]1.14881[/C][/ROW]
[ROW][C]281[/C][C]6[/C][C]3.95294[/C][C]2.04706[/C][/ROW]
[ROW][C]282[/C][C]8[/C][C]6.71231[/C][C]1.28769[/C][/ROW]
[ROW][C]283[/C][C]9.5[/C][C]7.70572[/C][C]1.79428[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.60989[/C][C]1.39011[/C][/ROW]
[ROW][C]285[/C][C]8[/C][C]5.5383[/C][C]2.4617[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]10.0695[/C][C]-1.06954[/C][/ROW]
[ROW][C]287[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268065&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268065&T=4

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	5.78472	1.71528
2	2.5	5.17108	-2.67108
3	6	5.22008	0.779924
4	6.5	5.80965	0.690348
5	1	5.32298	-4.32298
6	1	5.37982	-4.37982
7	5.5	5.78613	-0.286128
8	8.5	5.39061	3.10939
9	6.5	6.37951	0.120486
10	4.5	4.77114	-0.271136
11	2	7.28385	-5.28385
12	5	5.58769	-0.587688
13	0.5	6.67774	-6.17774
14	5	4.6704	0.3296
15	5	5.48682	-0.486824
16	2.5	4.19042	-1.69042
17	5	5.05603	-0.0560319
18	5.5	5.95938	-0.459376
19	3.5	5.41042	-1.91042
20	3	5.89152	-2.89152
21	4	4.60168	-0.601682
22	0.5	4.66346	-4.16346
23	6.5	5.78819	0.711807
24	4.5	5.59883	-1.09883
25	7.5	4.75112	2.74888
26	5.5	5.83466	-0.334662
27	4	5.74389	-1.74389
28	7.5	6.22463	1.27537
29	7	5.5306	1.4694
30	4	5.10366	-1.10366
31	5.5	4.86869	0.631309
32	2.5	4.65391	-2.15391
33	5.5	6.42305	-0.923049
34	0.5	4.54233	-4.04233
35	3.5	5.68973	-2.18973
36	2.5	6.88733	-4.38733
37	4.5	5.66586	-1.16586
38	4.5	5.9241	-1.4241
39	4.5	4.72289	-0.222895
40	6	5.63613	0.363869
41	2.5	5.41627	-2.91627
42	5	6.62317	-1.62317
43	0	5.21893	-5.21893
44	5	6.75334	-1.75334
45	6.5	5.15793	1.34207
46	5	6.02558	-1.02558
47	6	4.98143	1.01857
48	4.5	5.95334	-1.45334
49	5.5	5.62041	-0.120414
50	1	4.717	-3.717
51	7.5	4.25988	3.24012
52	6	4.95368	1.04632
53	5	5.10645	-0.106449
54	1	5.76172	-4.76172
55	5	6.19229	-1.19229
56	6.5	5.35891	1.14109
57	7	6.43702	0.562981
58	4.5	7.04582	-2.54582
59	0	4.55414	-4.55414
60	8.5	5.27501	3.22499
61	3.5	4.25482	-0.754815
62	7.5	6.03219	1.46781
63	3.5	6.09304	-2.59304
64	6	4.94835	1.05165
65	1.5	4.72919	-3.22919
66	9	5.99883	3.00117
67	3.5	4.94412	-1.44412
68	3.5	5.41778	-1.91778
69	4	5.61733	-1.61733
70	6.5	5.72048	0.779522
71	7.5	5.24251	2.25749
72	6	4.86359	1.13641
73	5	6.33138	-1.33138
74	5.5	5.38699	0.113009
75	3.5	5.79573	-2.29573
76	7.5	5.32811	2.17189
77	1	5.36295	-4.36295
78	6.5	5.26725	1.23275
79	NA	NA	0.894188
80	6.5	5.6911	0.808903
81	6.5	6.19081	0.309187
82	7	8.00088	-1.00088
83	3.5	7.30415	-3.80415
84	1.5	2.59598	-1.09598
85	4	0.727582	3.27242
86	7.5	8.23376	-0.733763
87	4.5	9.15552	-4.65552
88	0	0.795237	-0.795237
89	3.5	3.51777	-0.0177708
90	5.5	5.34417	0.155834
91	5	5.02726	-0.0272568
92	4.5	6.72854	-2.22854
93	2.5	-0.46874	2.96874
94	7.5	5.65636	1.84364
95	7	12.2853	-5.28535
96	0	0.696314	-0.696314
97	4.5	7.06502	-2.56502
98	3	6.91309	-3.91309
99	1.5	2.4656	-0.9656
100	3.5	7.1281	-3.6281
101	2.5	2.34955	0.150451
102	5.5	2.88466	2.61534
103	8	11.4683	-3.46834
104	1	1.30137	-0.301373
105	5	5.47154	-0.471543
106	4.5	5.83128	-1.33128
107	3	4.59985	-1.59985
108	3	0.169889	2.83011
109	8	9.53324	-1.53324
110	2.5	0.42274	2.07726
111	7	11.5728	-4.5728
112	0	4.14699	-4.14699
113	1	2.02235	-1.02235
114	3.5	2.57406	0.925937
115	5.5	4.95786	0.542137
116	5.5	9.96331	-4.46331
117	0.5	-0.717594	1.21759
118	7.5	5.10433	2.39567
119	9	6.58313	2.41687
120	9.5	9.88158	-0.381579
121	8.5	6.5035	1.9965
122	7	10.7029	-3.70288
123	8	5.16995	2.83005
124	10	11.6349	-1.63488
125	7	3.74908	3.25092
126	8.5	8.81473	-0.31473
127	9	5.14073	3.85927
128	9.5	12.2786	-2.7786
129	4	4.17945	-0.179449
130	6	5.27285	0.727147
131	8	10.3084	-2.30838
132	5.5	3.74953	1.75047
133	9.5	8.53128	0.968719
134	7.5	6.67358	0.826415
135	7	7.88889	-0.888886
136	7.5	5.09	2.41
137	8	7.12523	0.874773
138	7	6.58782	0.412185
139	7	8.43858	-1.43858
140	6	2.98936	3.01064
141	10	13.7321	-3.7321
142	2.5	2.15661	0.343386
143	9	10.4657	-1.4657
144	8	7.47064	0.529362
145	6	1.74712	4.25288
146	8.5	7.2416	1.2584
147	6	4.34957	1.65043
148	9	7.26616	1.73384
149	8	6.72574	1.27426
150	8	6.61452	1.38548
151	9	9.46082	-0.46082
152	5.5	6.00747	-0.507468
153	5	4.34331	0.656693
154	7	10.6769	-3.67692
155	5.5	4.83913	0.660866
156	9	13.3957	-4.39566
157	2	0.445665	1.55433
158	8.5	7.12274	1.37726
159	9	9.06037	-0.0603677
160	8.5	6.18495	2.31505
161	9	9.14653	-0.14653
162	7.5	5.95168	1.54832
163	10	8.23375	1.76625
164	9	10.8912	-1.89118
165	7.5	8.16783	-0.667833
166	6	1.93022	4.06978
167	10.5	11.3587	-0.858745
168	8.5	7.94621	0.553795
169	8	4.37592	3.62408
170	10	6.51135	3.48865
171	10.5	9.30039	1.19961
172	6.5	5.2621	1.2379
173	9.5	5.84441	3.65559
174	8.5	9.08523	-0.585229
175	7.5	9.58598	-2.08598
176	5	4.80577	0.194232
177	8	4.49104	3.50896
178	10	8.9737	1.0263
179	7	7.27018	-0.270184
180	7.5	7.80528	-0.305276
181	7.5	4.34555	3.15445
182	9.5	10.4989	-0.998903
183	6	4.05208	1.94792
184	10	8.77785	1.22215
185	7	10.2777	-3.27774
186	3	4.05677	-1.05677
187	6	6.05356	-0.0535571
188	7	5.54915	1.45085
189	10	9.48686	0.51314
190	7	8.9066	-1.9066
191	3.5	2.88426	0.615741
192	8	4.10609	3.89391
193	10	10.3135	-0.313511
194	5.5	3.54323	1.95677
195	6	5.38725	0.612749
196	6.5	6.35031	0.149695
197	6.5	3.54982	2.95018
198	8.5	10.1592	-1.65917
199	4	0.499835	3.50017
200	9.5	7.94749	1.55251
201	8	8.11342	-0.113418
202	8.5	11.487	-2.98703
203	5.5	4.88916	0.610845
204	7	3.38209	3.61791
205	9	6.92016	2.07984
206	8	7.21892	0.781078
207	10	8.5807	1.4193
208	8	8.04294	-0.0429437
209	6	4.95939	1.04061
210	8	8.39639	-0.39639
211	5	1.90899	3.09101
212	9	11.1777	-2.17774
213	4.5	2.74089	1.75911
214	8.5	8.25648	0.243523
215	7	4.61379	2.38621
216	9.5	8.08045	1.41955
217	8.5	6.18131	2.31869
218	7.5	6.54181	0.958195
219	7.5	9.30969	-1.80969
220	5	6.21673	-1.21673
221	7	7.56493	-0.564929
222	8	8.7609	-0.7609
223	5.5	3.38186	2.11814
224	8.5	8.13439	0.365607
225	7.5	5.08993	2.41007
226	9.5	8.65841	0.841586
227	7	7.43626	-0.436259
228	8	6.71584	1.28416
229	8.5	10.814	-2.31402
230	3.5	3.7054	-0.205399
231	6.5	4.89097	1.60903
232	6.5	3.37125	3.12875
233	10.5	8.1797	2.3203
234	8.5	6.77823	1.72177
235	8	4.43044	3.56956
236	10	7.32598	2.67402
237	10	7.62083	2.37917
238	9.5	5.28512	4.21488
239	9	8.44762	0.552384
240	10	8.05693	1.94307
241	7.5	8.55875	-1.05875
242	4.5	4.49959	0.000412841
243	4.5	9.97437	-5.47437
244	0.5	-0.692945	1.19294
245	6.5	9.14886	-2.64886
246	4.5	5.26766	-0.76766
247	5.5	5.38115	0.118845
248	5	6.73625	-1.73625
249	6	8.3352	-2.3352
250	4	1.36858	2.63142
251	8	4.61474	3.38526
252	10.5	7.96137	2.53863
253	8.5	8.52621	-0.0262149
254	6.5	6.07932	0.420679
255	8	7.19126	0.808741
256	8.5	9.6557	-1.1557
257	5.5	6.16279	-0.662791
258	7	7.61508	-0.615078
259	5	6.48057	-1.48057
260	3.5	5.3372	-1.8372
261	5	3.39211	1.60789
262	9	6.54574	2.45426
263	8.5	10.1948	-1.69482
264	5	4.00283	0.997167
265	9.5	10.8741	-1.37412
266	3	8.88506	-5.88506
267	1.5	-0.304453	1.80445
268	6	10.8767	-4.87666
269	0.5	0.301703	0.198297
270	6.5	4.95456	1.54544
271	7.5	8.53027	-1.03027
272	4.5	2.27068	2.22932
273	8	6.75044	1.24956
274	9	8.39784	0.602157
275	7.5	7.07694	0.423055
276	8.5	6.14148	2.35852
277	7	3.61275	3.38725
278	9.5	8.15786	1.34214
279	6.5	1.59767	4.90233
280	9.5	8.35119	1.14881
281	6	3.95294	2.04706
282	8	6.71231	1.28769
283	9.5	7.70572	1.79428
284	8	6.60989	1.39011
285	8	5.5383	2.4617
286	9	10.0695	-1.06954
287	5	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
17	0.312658	0.625317	0.687342
18	0.294718	0.589437	0.705282
19	0.176886	0.353772	0.823114
20	0.0993071	0.198614	0.900693
21	0.248041	0.496081	0.751959
22	0.171144	0.342289	0.828856
23	0.109204	0.218408	0.890796
24	0.0966523	0.193305	0.903348
25	0.0679891	0.135978	0.932011
26	0.0804227	0.160845	0.919577
27	0.0518832	0.103766	0.948117
28	0.0419219	0.0838438	0.958078
29	0.0319409	0.0638818	0.968059
30	0.0199673	0.0399345	0.980033
31	0.0120553	0.0241105	0.987945
32	0.0161707	0.0323415	0.983829
33	0.0103584	0.0207168	0.989642
34	0.00774815	0.0154963	0.992252
35	0.00472332	0.00944663	0.995277
36	0.0932805	0.186561	0.906719
37	0.0852894	0.170579	0.914711
38	0.125584	0.251169	0.874416
39	0.0958724	0.191745	0.904128
40	0.0794964	0.158993	0.920504
41	0.182759	0.365517	0.817241
42	0.17815	0.356299	0.82185
43	0.308503	0.617006	0.691497
44	0.321147	0.642293	0.678853
45	0.297046	0.594091	0.702954
46	0.268211	0.536422	0.731789
47	0.226412	0.452823	0.773588
48	0.200417	0.400835	0.799583
49	0.192827	0.385654	0.807173
50	0.218451	0.436903	0.781549
51	0.281262	0.562524	0.718738
52	0.343037	0.686074	0.656963
53	0.314458	0.628915	0.685542
54	0.380118	0.760236	0.619882
55	0.386049	0.772099	0.613951
56	0.452245	0.904489	0.547755
57	0.511635	0.97673	0.488365
58	0.477964	0.955927	0.522036
59	0.61709	0.765819	0.38291
60	0.638287	0.723427	0.361713
61	0.596591	0.806818	0.403409
62	0.649668	0.700663	0.350332
63	0.640951	0.718097	0.359049
64	0.618572	0.762857	0.381428
65	0.720703	0.558593	0.279297
66	0.764218	0.471564	0.235782
67	0.755861	0.488278	0.244139
68	0.731601	0.536799	0.268399
69	0.710042	0.579916	0.289958
70	0.682323	0.635354	0.317677
71	0.677805	0.64439	0.322195
72	0.654428	0.691143	0.345572
73	0.633123	0.733753	0.366877
74	0.594717	0.810566	0.405283
75	0.568977	0.862045	0.431023
76	0.579438	0.841123	0.420562
77	0.690524	0.618951	0.309476
78	0.664579	0.670843	0.335421
79	0.650071	0.699858	0.349929
80	0.630961	0.738077	0.369039
81	0.628546	0.742909	0.371454
82	0.59844	0.80312	0.40156
83	0.650977	0.698046	0.349023
84	0.62322	0.75356	0.37678
85	0.65728	0.68544	0.34272
86	0.628822	0.742355	0.371178
87	0.725116	0.549769	0.274884
88	0.710656	0.578687	0.289344
89	0.683879	0.632243	0.316121
90	0.652566	0.694868	0.347434
91	0.627724	0.744552	0.372276
92	0.629145	0.74171	0.370855
93	0.657912	0.684176	0.342088
94	0.669475	0.66105	0.330525
95	0.798079	0.403842	0.201921
96	0.779996	0.440008	0.220004
97	0.771607	0.456787	0.228393
98	0.798511	0.402978	0.201489
99	0.784638	0.430725	0.215362
100	0.813815	0.372371	0.186185
101	0.801304	0.397392	0.198696
102	0.841981	0.316037	0.158019
103	0.889967	0.220065	0.110033
104	0.877998	0.244004	0.122002
105	0.865846	0.268309	0.134154
106	0.862146	0.275707	0.137854
107	0.868436	0.263128	0.131564
108	0.889731	0.220539	0.110269
109	0.891871	0.216259	0.108129
110	0.895545	0.20891	0.104455
111	0.950042	0.0999166	0.0499583
112	0.96831	0.0633805	0.0316903
113	0.968996	0.0620083	0.0310042
114	0.96614	0.06772	0.03386
115	0.962575	0.0748493	0.0374247
116	0.976393	0.0472142	0.0236071
117	0.98038	0.0392406	0.0196203
118	0.985664	0.0286723	0.0143362
119	0.988958	0.0220832	0.0110416
120	0.986988	0.0260249	0.0130125
121	0.991291	0.0174183	0.00870916
122	0.990352	0.0192962	0.00964809
123	0.991414	0.0171729	0.00858644
124	0.992234	0.0155327	0.00776637
125	0.995452	0.00909673	0.00454836
126	0.994436	0.0111283	0.00556416
127	0.997551	0.00489794	0.00244897
128	0.997829	0.00434181	0.00217091
129	0.997164	0.00567274	0.00283637
130	0.99675	0.00650072	0.00325036
131	0.996452	0.0070962	0.0035481
132	0.99572	0.00856022	0.00428011
133	0.995017	0.00996664	0.00498332
134	0.993942	0.0121168	0.0060584
135	0.992855	0.0142892	0.00714462
136	0.99376	0.01248	0.00624002
137	0.992443	0.015114	0.00755699
138	0.990815	0.0183697	0.00918483
139	0.989128	0.0217447	0.0108724
140	0.991405	0.01719	0.00859499
141	0.9937	0.0126006	0.00630032
142	0.992172	0.015657	0.00782849
143	0.990153	0.0196934	0.00984669
144	0.988432	0.0231364	0.0115682
145	0.99183	0.0163398	0.00816992
146	0.989988	0.0200242	0.0100121
147	0.989912	0.0201752	0.0100876
148	0.989069	0.0218616	0.0109308
149	0.986504	0.026992	0.013496
150	0.984448	0.0311039	0.0155519
151	0.982216	0.0355676	0.0177838
152	0.980001	0.0399989	0.0199995
153	0.975791	0.0484178	0.0242089
154	0.977971	0.0440576	0.0220288
155	0.974669	0.0506627	0.0253313
156	0.988085	0.0238303	0.0119152
157	0.986361	0.027278	0.013639
158	0.984481	0.0310373	0.0155187
159	0.980634	0.0387329	0.0193664
160	0.982699	0.0346024	0.0173012
161	0.978884	0.042231	0.0211155
162	0.975648	0.0487037	0.0243518
163	0.974139	0.0517223	0.0258611
164	0.97271	0.0545793	0.0272897
165	0.96828	0.0634396	0.0317198
166	0.974311	0.0513783	0.0256891
167	0.968993	0.0620133	0.0310067
168	0.966097	0.067805	0.0339025
169	0.981722	0.0365569	0.0182785
170	0.982602	0.0347961	0.017398
171	0.981116	0.037768	0.018884
172	0.977604	0.0447925	0.0223962
173	0.982807	0.0343867	0.0171934
174	0.97865	0.0426994	0.0213497
175	0.978656	0.0426882	0.0213441
176	0.973562	0.052876	0.026438
177	0.97813	0.0437399	0.02187
178	0.973939	0.052123	0.0260615
179	0.968172	0.0636559	0.031828
180	0.961004	0.0779922	0.0389961
181	0.963663	0.0726734	0.0363367
182	0.959897	0.0802056	0.0401028
183	0.958287	0.0834251	0.0417125
184	0.952623	0.0947545	0.0473772
185	0.956551	0.0868978	0.0434489
186	0.958279	0.0834421	0.0417211
187	0.949913	0.100173	0.0500867
188	0.94415	0.1117	0.0558498
189	0.934096	0.131807	0.0659037
190	0.94188	0.116241	0.0581204
191	0.931505	0.13699	0.0684949
192	0.951594	0.0968117	0.0484059
193	0.945282	0.109437	0.0547184
194	0.937094	0.125813	0.0629064
195	0.925401	0.149198	0.0745988
196	0.910774	0.178452	0.0892262
197	0.909194	0.181613	0.0908065
198	0.917835	0.16433	0.082165
199	0.931529	0.136941	0.0684705
200	0.920532	0.158935	0.0794675
201	0.905874	0.188252	0.0941259
202	0.918881	0.162237	0.0811186
203	0.90473	0.190541	0.0952704
204	0.917529	0.164942	0.0824712
205	0.905949	0.188101	0.0940506
206	0.888418	0.223164	0.111582
207	0.876496	0.247008	0.123504
208	0.861219	0.277563	0.138781
209	0.84717	0.30566	0.15283
210	0.828581	0.342837	0.171419
211	0.831967	0.336066	0.168033
212	0.818409	0.363181	0.181591
213	0.815549	0.368902	0.184451
214	0.785767	0.428465	0.214233
215	0.773617	0.452767	0.226383
216	0.74351	0.51298	0.25649
217	0.724075	0.551851	0.275925
218	0.686952	0.626097	0.313048
219	0.689467	0.621066	0.310533
220	0.660145	0.679709	0.339855
221	0.634255	0.731489	0.365745
222	0.599557	0.800886	0.400443
223	0.573439	0.853122	0.426561
224	0.528827	0.942346	0.471173
225	0.507823	0.984355	0.492177
226	0.46516	0.930321	0.53484
227	0.420878	0.841756	0.579122
228	0.392742	0.785483	0.607258
229	0.380939	0.761878	0.619061
230	0.33748	0.67496	0.66252
231	0.311469	0.622937	0.688531
232	0.327762	0.655523	0.672238
233	0.370467	0.740934	0.629533
234	0.358505	0.71701	0.641495
235	0.407786	0.815571	0.592214
236	0.370838	0.741675	0.629162
237	0.37314	0.74628	0.62686
238	0.462546	0.925093	0.537454
239	0.413996	0.827993	0.586004
240	0.384666	0.769331	0.615334
241	0.353397	0.706795	0.646603
242	0.3205	0.641	0.6795
243	0.578781	0.842437	0.421219
244	0.569346	0.861308	0.430654
245	0.541367	0.917266	0.458633
246	0.485081	0.970161	0.514919
247	0.44367	0.887341	0.55633
248	0.421225	0.842449	0.578775
249	0.3845	0.768999	0.6155
250	0.343121	0.686241	0.656879
251	0.330906	0.661812	0.669094
252	0.387229	0.774459	0.612771
253	0.373676	0.747351	0.626324
254	0.315612	0.631224	0.684388
255	0.261985	0.523969	0.738015
256	0.209831	0.419662	0.790169
257	0.202389	0.404779	0.797611
258	0.156026	0.312051	0.843974
259	0.14097	0.28194	0.85903
260	0.111263	0.222525	0.888737
261	0.0809815	0.161963	0.919019
262	0.0837168	0.167434	0.916283
263	0.0556105	0.111221	0.944389
264	0.0398098	0.0796195	0.96019
265	0.0477781	0.0955562	0.952222
266	0.684511	0.630979	0.315489
267	0.763087	0.473827	0.236913
268	0.940811	0.118379	0.0591894
269	0.991889	0.0162222	0.00811108
270	0.97768	0.0446403	0.0223201

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
17 & 0.312658 & 0.625317 & 0.687342 \tabularnewline
18 & 0.294718 & 0.589437 & 0.705282 \tabularnewline
19 & 0.176886 & 0.353772 & 0.823114 \tabularnewline
20 & 0.0993071 & 0.198614 & 0.900693 \tabularnewline
21 & 0.248041 & 0.496081 & 0.751959 \tabularnewline
22 & 0.171144 & 0.342289 & 0.828856 \tabularnewline
23 & 0.109204 & 0.218408 & 0.890796 \tabularnewline
24 & 0.0966523 & 0.193305 & 0.903348 \tabularnewline
25 & 0.0679891 & 0.135978 & 0.932011 \tabularnewline
26 & 0.0804227 & 0.160845 & 0.919577 \tabularnewline
27 & 0.0518832 & 0.103766 & 0.948117 \tabularnewline
28 & 0.0419219 & 0.0838438 & 0.958078 \tabularnewline
29 & 0.0319409 & 0.0638818 & 0.968059 \tabularnewline
30 & 0.0199673 & 0.0399345 & 0.980033 \tabularnewline
31 & 0.0120553 & 0.0241105 & 0.987945 \tabularnewline
32 & 0.0161707 & 0.0323415 & 0.983829 \tabularnewline
33 & 0.0103584 & 0.0207168 & 0.989642 \tabularnewline
34 & 0.00774815 & 0.0154963 & 0.992252 \tabularnewline
35 & 0.00472332 & 0.00944663 & 0.995277 \tabularnewline
36 & 0.0932805 & 0.186561 & 0.906719 \tabularnewline
37 & 0.0852894 & 0.170579 & 0.914711 \tabularnewline
38 & 0.125584 & 0.251169 & 0.874416 \tabularnewline
39 & 0.0958724 & 0.191745 & 0.904128 \tabularnewline
40 & 0.0794964 & 0.158993 & 0.920504 \tabularnewline
41 & 0.182759 & 0.365517 & 0.817241 \tabularnewline
42 & 0.17815 & 0.356299 & 0.82185 \tabularnewline
43 & 0.308503 & 0.617006 & 0.691497 \tabularnewline
44 & 0.321147 & 0.642293 & 0.678853 \tabularnewline
45 & 0.297046 & 0.594091 & 0.702954 \tabularnewline
46 & 0.268211 & 0.536422 & 0.731789 \tabularnewline
47 & 0.226412 & 0.452823 & 0.773588 \tabularnewline
48 & 0.200417 & 0.400835 & 0.799583 \tabularnewline
49 & 0.192827 & 0.385654 & 0.807173 \tabularnewline
50 & 0.218451 & 0.436903 & 0.781549 \tabularnewline
51 & 0.281262 & 0.562524 & 0.718738 \tabularnewline
52 & 0.343037 & 0.686074 & 0.656963 \tabularnewline
53 & 0.314458 & 0.628915 & 0.685542 \tabularnewline
54 & 0.380118 & 0.760236 & 0.619882 \tabularnewline
55 & 0.386049 & 0.772099 & 0.613951 \tabularnewline
56 & 0.452245 & 0.904489 & 0.547755 \tabularnewline
57 & 0.511635 & 0.97673 & 0.488365 \tabularnewline
58 & 0.477964 & 0.955927 & 0.522036 \tabularnewline
59 & 0.61709 & 0.765819 & 0.38291 \tabularnewline
60 & 0.638287 & 0.723427 & 0.361713 \tabularnewline
61 & 0.596591 & 0.806818 & 0.403409 \tabularnewline
62 & 0.649668 & 0.700663 & 0.350332 \tabularnewline
63 & 0.640951 & 0.718097 & 0.359049 \tabularnewline
64 & 0.618572 & 0.762857 & 0.381428 \tabularnewline
65 & 0.720703 & 0.558593 & 0.279297 \tabularnewline
66 & 0.764218 & 0.471564 & 0.235782 \tabularnewline
67 & 0.755861 & 0.488278 & 0.244139 \tabularnewline
68 & 0.731601 & 0.536799 & 0.268399 \tabularnewline
69 & 0.710042 & 0.579916 & 0.289958 \tabularnewline
70 & 0.682323 & 0.635354 & 0.317677 \tabularnewline
71 & 0.677805 & 0.64439 & 0.322195 \tabularnewline
72 & 0.654428 & 0.691143 & 0.345572 \tabularnewline
73 & 0.633123 & 0.733753 & 0.366877 \tabularnewline
74 & 0.594717 & 0.810566 & 0.405283 \tabularnewline
75 & 0.568977 & 0.862045 & 0.431023 \tabularnewline
76 & 0.579438 & 0.841123 & 0.420562 \tabularnewline
77 & 0.690524 & 0.618951 & 0.309476 \tabularnewline
78 & 0.664579 & 0.670843 & 0.335421 \tabularnewline
79 & 0.650071 & 0.699858 & 0.349929 \tabularnewline
80 & 0.630961 & 0.738077 & 0.369039 \tabularnewline
81 & 0.628546 & 0.742909 & 0.371454 \tabularnewline
82 & 0.59844 & 0.80312 & 0.40156 \tabularnewline
83 & 0.650977 & 0.698046 & 0.349023 \tabularnewline
84 & 0.62322 & 0.75356 & 0.37678 \tabularnewline
85 & 0.65728 & 0.68544 & 0.34272 \tabularnewline
86 & 0.628822 & 0.742355 & 0.371178 \tabularnewline
87 & 0.725116 & 0.549769 & 0.274884 \tabularnewline
88 & 0.710656 & 0.578687 & 0.289344 \tabularnewline
89 & 0.683879 & 0.632243 & 0.316121 \tabularnewline
90 & 0.652566 & 0.694868 & 0.347434 \tabularnewline
91 & 0.627724 & 0.744552 & 0.372276 \tabularnewline
92 & 0.629145 & 0.74171 & 0.370855 \tabularnewline
93 & 0.657912 & 0.684176 & 0.342088 \tabularnewline
94 & 0.669475 & 0.66105 & 0.330525 \tabularnewline
95 & 0.798079 & 0.403842 & 0.201921 \tabularnewline
96 & 0.779996 & 0.440008 & 0.220004 \tabularnewline
97 & 0.771607 & 0.456787 & 0.228393 \tabularnewline
98 & 0.798511 & 0.402978 & 0.201489 \tabularnewline
99 & 0.784638 & 0.430725 & 0.215362 \tabularnewline
100 & 0.813815 & 0.372371 & 0.186185 \tabularnewline
101 & 0.801304 & 0.397392 & 0.198696 \tabularnewline
102 & 0.841981 & 0.316037 & 0.158019 \tabularnewline
103 & 0.889967 & 0.220065 & 0.110033 \tabularnewline
104 & 0.877998 & 0.244004 & 0.122002 \tabularnewline
105 & 0.865846 & 0.268309 & 0.134154 \tabularnewline
106 & 0.862146 & 0.275707 & 0.137854 \tabularnewline
107 & 0.868436 & 0.263128 & 0.131564 \tabularnewline
108 & 0.889731 & 0.220539 & 0.110269 \tabularnewline
109 & 0.891871 & 0.216259 & 0.108129 \tabularnewline
110 & 0.895545 & 0.20891 & 0.104455 \tabularnewline
111 & 0.950042 & 0.0999166 & 0.0499583 \tabularnewline
112 & 0.96831 & 0.0633805 & 0.0316903 \tabularnewline
113 & 0.968996 & 0.0620083 & 0.0310042 \tabularnewline
114 & 0.96614 & 0.06772 & 0.03386 \tabularnewline
115 & 0.962575 & 0.0748493 & 0.0374247 \tabularnewline
116 & 0.976393 & 0.0472142 & 0.0236071 \tabularnewline
117 & 0.98038 & 0.0392406 & 0.0196203 \tabularnewline
118 & 0.985664 & 0.0286723 & 0.0143362 \tabularnewline
119 & 0.988958 & 0.0220832 & 0.0110416 \tabularnewline
120 & 0.986988 & 0.0260249 & 0.0130125 \tabularnewline
121 & 0.991291 & 0.0174183 & 0.00870916 \tabularnewline
122 & 0.990352 & 0.0192962 & 0.00964809 \tabularnewline
123 & 0.991414 & 0.0171729 & 0.00858644 \tabularnewline
124 & 0.992234 & 0.0155327 & 0.00776637 \tabularnewline
125 & 0.995452 & 0.00909673 & 0.00454836 \tabularnewline
126 & 0.994436 & 0.0111283 & 0.00556416 \tabularnewline
127 & 0.997551 & 0.00489794 & 0.00244897 \tabularnewline
128 & 0.997829 & 0.00434181 & 0.00217091 \tabularnewline
129 & 0.997164 & 0.00567274 & 0.00283637 \tabularnewline
130 & 0.99675 & 0.00650072 & 0.00325036 \tabularnewline
131 & 0.996452 & 0.0070962 & 0.0035481 \tabularnewline
132 & 0.99572 & 0.00856022 & 0.00428011 \tabularnewline
133 & 0.995017 & 0.00996664 & 0.00498332 \tabularnewline
134 & 0.993942 & 0.0121168 & 0.0060584 \tabularnewline
135 & 0.992855 & 0.0142892 & 0.00714462 \tabularnewline
136 & 0.99376 & 0.01248 & 0.00624002 \tabularnewline
137 & 0.992443 & 0.015114 & 0.00755699 \tabularnewline
138 & 0.990815 & 0.0183697 & 0.00918483 \tabularnewline
139 & 0.989128 & 0.0217447 & 0.0108724 \tabularnewline
140 & 0.991405 & 0.01719 & 0.00859499 \tabularnewline
141 & 0.9937 & 0.0126006 & 0.00630032 \tabularnewline
142 & 0.992172 & 0.015657 & 0.00782849 \tabularnewline
143 & 0.990153 & 0.0196934 & 0.00984669 \tabularnewline
144 & 0.988432 & 0.0231364 & 0.0115682 \tabularnewline
145 & 0.99183 & 0.0163398 & 0.00816992 \tabularnewline
146 & 0.989988 & 0.0200242 & 0.0100121 \tabularnewline
147 & 0.989912 & 0.0201752 & 0.0100876 \tabularnewline
148 & 0.989069 & 0.0218616 & 0.0109308 \tabularnewline
149 & 0.986504 & 0.026992 & 0.013496 \tabularnewline
150 & 0.984448 & 0.0311039 & 0.0155519 \tabularnewline
151 & 0.982216 & 0.0355676 & 0.0177838 \tabularnewline
152 & 0.980001 & 0.0399989 & 0.0199995 \tabularnewline
153 & 0.975791 & 0.0484178 & 0.0242089 \tabularnewline
154 & 0.977971 & 0.0440576 & 0.0220288 \tabularnewline
155 & 0.974669 & 0.0506627 & 0.0253313 \tabularnewline
156 & 0.988085 & 0.0238303 & 0.0119152 \tabularnewline
157 & 0.986361 & 0.027278 & 0.013639 \tabularnewline
158 & 0.984481 & 0.0310373 & 0.0155187 \tabularnewline
159 & 0.980634 & 0.0387329 & 0.0193664 \tabularnewline
160 & 0.982699 & 0.0346024 & 0.0173012 \tabularnewline
161 & 0.978884 & 0.042231 & 0.0211155 \tabularnewline
162 & 0.975648 & 0.0487037 & 0.0243518 \tabularnewline
163 & 0.974139 & 0.0517223 & 0.0258611 \tabularnewline
164 & 0.97271 & 0.0545793 & 0.0272897 \tabularnewline
165 & 0.96828 & 0.0634396 & 0.0317198 \tabularnewline
166 & 0.974311 & 0.0513783 & 0.0256891 \tabularnewline
167 & 0.968993 & 0.0620133 & 0.0310067 \tabularnewline
168 & 0.966097 & 0.067805 & 0.0339025 \tabularnewline
169 & 0.981722 & 0.0365569 & 0.0182785 \tabularnewline
170 & 0.982602 & 0.0347961 & 0.017398 \tabularnewline
171 & 0.981116 & 0.037768 & 0.018884 \tabularnewline
172 & 0.977604 & 0.0447925 & 0.0223962 \tabularnewline
173 & 0.982807 & 0.0343867 & 0.0171934 \tabularnewline
174 & 0.97865 & 0.0426994 & 0.0213497 \tabularnewline
175 & 0.978656 & 0.0426882 & 0.0213441 \tabularnewline
176 & 0.973562 & 0.052876 & 0.026438 \tabularnewline
177 & 0.97813 & 0.0437399 & 0.02187 \tabularnewline
178 & 0.973939 & 0.052123 & 0.0260615 \tabularnewline
179 & 0.968172 & 0.0636559 & 0.031828 \tabularnewline
180 & 0.961004 & 0.0779922 & 0.0389961 \tabularnewline
181 & 0.963663 & 0.0726734 & 0.0363367 \tabularnewline
182 & 0.959897 & 0.0802056 & 0.0401028 \tabularnewline
183 & 0.958287 & 0.0834251 & 0.0417125 \tabularnewline
184 & 0.952623 & 0.0947545 & 0.0473772 \tabularnewline
185 & 0.956551 & 0.0868978 & 0.0434489 \tabularnewline
186 & 0.958279 & 0.0834421 & 0.0417211 \tabularnewline
187 & 0.949913 & 0.100173 & 0.0500867 \tabularnewline
188 & 0.94415 & 0.1117 & 0.0558498 \tabularnewline
189 & 0.934096 & 0.131807 & 0.0659037 \tabularnewline
190 & 0.94188 & 0.116241 & 0.0581204 \tabularnewline
191 & 0.931505 & 0.13699 & 0.0684949 \tabularnewline
192 & 0.951594 & 0.0968117 & 0.0484059 \tabularnewline
193 & 0.945282 & 0.109437 & 0.0547184 \tabularnewline
194 & 0.937094 & 0.125813 & 0.0629064 \tabularnewline
195 & 0.925401 & 0.149198 & 0.0745988 \tabularnewline
196 & 0.910774 & 0.178452 & 0.0892262 \tabularnewline
197 & 0.909194 & 0.181613 & 0.0908065 \tabularnewline
198 & 0.917835 & 0.16433 & 0.082165 \tabularnewline
199 & 0.931529 & 0.136941 & 0.0684705 \tabularnewline
200 & 0.920532 & 0.158935 & 0.0794675 \tabularnewline
201 & 0.905874 & 0.188252 & 0.0941259 \tabularnewline
202 & 0.918881 & 0.162237 & 0.0811186 \tabularnewline
203 & 0.90473 & 0.190541 & 0.0952704 \tabularnewline
204 & 0.917529 & 0.164942 & 0.0824712 \tabularnewline
205 & 0.905949 & 0.188101 & 0.0940506 \tabularnewline
206 & 0.888418 & 0.223164 & 0.111582 \tabularnewline
207 & 0.876496 & 0.247008 & 0.123504 \tabularnewline
208 & 0.861219 & 0.277563 & 0.138781 \tabularnewline
209 & 0.84717 & 0.30566 & 0.15283 \tabularnewline
210 & 0.828581 & 0.342837 & 0.171419 \tabularnewline
211 & 0.831967 & 0.336066 & 0.168033 \tabularnewline
212 & 0.818409 & 0.363181 & 0.181591 \tabularnewline
213 & 0.815549 & 0.368902 & 0.184451 \tabularnewline
214 & 0.785767 & 0.428465 & 0.214233 \tabularnewline
215 & 0.773617 & 0.452767 & 0.226383 \tabularnewline
216 & 0.74351 & 0.51298 & 0.25649 \tabularnewline
217 & 0.724075 & 0.551851 & 0.275925 \tabularnewline
218 & 0.686952 & 0.626097 & 0.313048 \tabularnewline
219 & 0.689467 & 0.621066 & 0.310533 \tabularnewline
220 & 0.660145 & 0.679709 & 0.339855 \tabularnewline
221 & 0.634255 & 0.731489 & 0.365745 \tabularnewline
222 & 0.599557 & 0.800886 & 0.400443 \tabularnewline
223 & 0.573439 & 0.853122 & 0.426561 \tabularnewline
224 & 0.528827 & 0.942346 & 0.471173 \tabularnewline
225 & 0.507823 & 0.984355 & 0.492177 \tabularnewline
226 & 0.46516 & 0.930321 & 0.53484 \tabularnewline
227 & 0.420878 & 0.841756 & 0.579122 \tabularnewline
228 & 0.392742 & 0.785483 & 0.607258 \tabularnewline
229 & 0.380939 & 0.761878 & 0.619061 \tabularnewline
230 & 0.33748 & 0.67496 & 0.66252 \tabularnewline
231 & 0.311469 & 0.622937 & 0.688531 \tabularnewline
232 & 0.327762 & 0.655523 & 0.672238 \tabularnewline
233 & 0.370467 & 0.740934 & 0.629533 \tabularnewline
234 & 0.358505 & 0.71701 & 0.641495 \tabularnewline
235 & 0.407786 & 0.815571 & 0.592214 \tabularnewline
236 & 0.370838 & 0.741675 & 0.629162 \tabularnewline
237 & 0.37314 & 0.74628 & 0.62686 \tabularnewline
238 & 0.462546 & 0.925093 & 0.537454 \tabularnewline
239 & 0.413996 & 0.827993 & 0.586004 \tabularnewline
240 & 0.384666 & 0.769331 & 0.615334 \tabularnewline
241 & 0.353397 & 0.706795 & 0.646603 \tabularnewline
242 & 0.3205 & 0.641 & 0.6795 \tabularnewline
243 & 0.578781 & 0.842437 & 0.421219 \tabularnewline
244 & 0.569346 & 0.861308 & 0.430654 \tabularnewline
245 & 0.541367 & 0.917266 & 0.458633 \tabularnewline
246 & 0.485081 & 0.970161 & 0.514919 \tabularnewline
247 & 0.44367 & 0.887341 & 0.55633 \tabularnewline
248 & 0.421225 & 0.842449 & 0.578775 \tabularnewline
249 & 0.3845 & 0.768999 & 0.6155 \tabularnewline
250 & 0.343121 & 0.686241 & 0.656879 \tabularnewline
251 & 0.330906 & 0.661812 & 0.669094 \tabularnewline
252 & 0.387229 & 0.774459 & 0.612771 \tabularnewline
253 & 0.373676 & 0.747351 & 0.626324 \tabularnewline
254 & 0.315612 & 0.631224 & 0.684388 \tabularnewline
255 & 0.261985 & 0.523969 & 0.738015 \tabularnewline
256 & 0.209831 & 0.419662 & 0.790169 \tabularnewline
257 & 0.202389 & 0.404779 & 0.797611 \tabularnewline
258 & 0.156026 & 0.312051 & 0.843974 \tabularnewline
259 & 0.14097 & 0.28194 & 0.85903 \tabularnewline
260 & 0.111263 & 0.222525 & 0.888737 \tabularnewline
261 & 0.0809815 & 0.161963 & 0.919019 \tabularnewline
262 & 0.0837168 & 0.167434 & 0.916283 \tabularnewline
263 & 0.0556105 & 0.111221 & 0.944389 \tabularnewline
264 & 0.0398098 & 0.0796195 & 0.96019 \tabularnewline
265 & 0.0477781 & 0.0955562 & 0.952222 \tabularnewline
266 & 0.684511 & 0.630979 & 0.315489 \tabularnewline
267 & 0.763087 & 0.473827 & 0.236913 \tabularnewline
268 & 0.940811 & 0.118379 & 0.0591894 \tabularnewline
269 & 0.991889 & 0.0162222 & 0.00811108 \tabularnewline
270 & 0.97768 & 0.0446403 & 0.0223201 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268065&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]17[/C][C]0.312658[/C][C]0.625317[/C][C]0.687342[/C][/ROW]
[ROW][C]18[/C][C]0.294718[/C][C]0.589437[/C][C]0.705282[/C][/ROW]
[ROW][C]19[/C][C]0.176886[/C][C]0.353772[/C][C]0.823114[/C][/ROW]
[ROW][C]20[/C][C]0.0993071[/C][C]0.198614[/C][C]0.900693[/C][/ROW]
[ROW][C]21[/C][C]0.248041[/C][C]0.496081[/C][C]0.751959[/C][/ROW]
[ROW][C]22[/C][C]0.171144[/C][C]0.342289[/C][C]0.828856[/C][/ROW]
[ROW][C]23[/C][C]0.109204[/C][C]0.218408[/C][C]0.890796[/C][/ROW]
[ROW][C]24[/C][C]0.0966523[/C][C]0.193305[/C][C]0.903348[/C][/ROW]
[ROW][C]25[/C][C]0.0679891[/C][C]0.135978[/C][C]0.932011[/C][/ROW]
[ROW][C]26[/C][C]0.0804227[/C][C]0.160845[/C][C]0.919577[/C][/ROW]
[ROW][C]27[/C][C]0.0518832[/C][C]0.103766[/C][C]0.948117[/C][/ROW]
[ROW][C]28[/C][C]0.0419219[/C][C]0.0838438[/C][C]0.958078[/C][/ROW]
[ROW][C]29[/C][C]0.0319409[/C][C]0.0638818[/C][C]0.968059[/C][/ROW]
[ROW][C]30[/C][C]0.0199673[/C][C]0.0399345[/C][C]0.980033[/C][/ROW]
[ROW][C]31[/C][C]0.0120553[/C][C]0.0241105[/C][C]0.987945[/C][/ROW]
[ROW][C]32[/C][C]0.0161707[/C][C]0.0323415[/C][C]0.983829[/C][/ROW]
[ROW][C]33[/C][C]0.0103584[/C][C]0.0207168[/C][C]0.989642[/C][/ROW]
[ROW][C]34[/C][C]0.00774815[/C][C]0.0154963[/C][C]0.992252[/C][/ROW]
[ROW][C]35[/C][C]0.00472332[/C][C]0.00944663[/C][C]0.995277[/C][/ROW]
[ROW][C]36[/C][C]0.0932805[/C][C]0.186561[/C][C]0.906719[/C][/ROW]
[ROW][C]37[/C][C]0.0852894[/C][C]0.170579[/C][C]0.914711[/C][/ROW]
[ROW][C]38[/C][C]0.125584[/C][C]0.251169[/C][C]0.874416[/C][/ROW]
[ROW][C]39[/C][C]0.0958724[/C][C]0.191745[/C][C]0.904128[/C][/ROW]
[ROW][C]40[/C][C]0.0794964[/C][C]0.158993[/C][C]0.920504[/C][/ROW]
[ROW][C]41[/C][C]0.182759[/C][C]0.365517[/C][C]0.817241[/C][/ROW]
[ROW][C]42[/C][C]0.17815[/C][C]0.356299[/C][C]0.82185[/C][/ROW]
[ROW][C]43[/C][C]0.308503[/C][C]0.617006[/C][C]0.691497[/C][/ROW]
[ROW][C]44[/C][C]0.321147[/C][C]0.642293[/C][C]0.678853[/C][/ROW]
[ROW][C]45[/C][C]0.297046[/C][C]0.594091[/C][C]0.702954[/C][/ROW]
[ROW][C]46[/C][C]0.268211[/C][C]0.536422[/C][C]0.731789[/C][/ROW]
[ROW][C]47[/C][C]0.226412[/C][C]0.452823[/C][C]0.773588[/C][/ROW]
[ROW][C]48[/C][C]0.200417[/C][C]0.400835[/C][C]0.799583[/C][/ROW]
[ROW][C]49[/C][C]0.192827[/C][C]0.385654[/C][C]0.807173[/C][/ROW]
[ROW][C]50[/C][C]0.218451[/C][C]0.436903[/C][C]0.781549[/C][/ROW]
[ROW][C]51[/C][C]0.281262[/C][C]0.562524[/C][C]0.718738[/C][/ROW]
[ROW][C]52[/C][C]0.343037[/C][C]0.686074[/C][C]0.656963[/C][/ROW]
[ROW][C]53[/C][C]0.314458[/C][C]0.628915[/C][C]0.685542[/C][/ROW]
[ROW][C]54[/C][C]0.380118[/C][C]0.760236[/C][C]0.619882[/C][/ROW]
[ROW][C]55[/C][C]0.386049[/C][C]0.772099[/C][C]0.613951[/C][/ROW]
[ROW][C]56[/C][C]0.452245[/C][C]0.904489[/C][C]0.547755[/C][/ROW]
[ROW][C]57[/C][C]0.511635[/C][C]0.97673[/C][C]0.488365[/C][/ROW]
[ROW][C]58[/C][C]0.477964[/C][C]0.955927[/C][C]0.522036[/C][/ROW]
[ROW][C]59[/C][C]0.61709[/C][C]0.765819[/C][C]0.38291[/C][/ROW]
[ROW][C]60[/C][C]0.638287[/C][C]0.723427[/C][C]0.361713[/C][/ROW]
[ROW][C]61[/C][C]0.596591[/C][C]0.806818[/C][C]0.403409[/C][/ROW]
[ROW][C]62[/C][C]0.649668[/C][C]0.700663[/C][C]0.350332[/C][/ROW]
[ROW][C]63[/C][C]0.640951[/C][C]0.718097[/C][C]0.359049[/C][/ROW]
[ROW][C]64[/C][C]0.618572[/C][C]0.762857[/C][C]0.381428[/C][/ROW]
[ROW][C]65[/C][C]0.720703[/C][C]0.558593[/C][C]0.279297[/C][/ROW]
[ROW][C]66[/C][C]0.764218[/C][C]0.471564[/C][C]0.235782[/C][/ROW]
[ROW][C]67[/C][C]0.755861[/C][C]0.488278[/C][C]0.244139[/C][/ROW]
[ROW][C]68[/C][C]0.731601[/C][C]0.536799[/C][C]0.268399[/C][/ROW]
[ROW][C]69[/C][C]0.710042[/C][C]0.579916[/C][C]0.289958[/C][/ROW]
[ROW][C]70[/C][C]0.682323[/C][C]0.635354[/C][C]0.317677[/C][/ROW]
[ROW][C]71[/C][C]0.677805[/C][C]0.64439[/C][C]0.322195[/C][/ROW]
[ROW][C]72[/C][C]0.654428[/C][C]0.691143[/C][C]0.345572[/C][/ROW]
[ROW][C]73[/C][C]0.633123[/C][C]0.733753[/C][C]0.366877[/C][/ROW]
[ROW][C]74[/C][C]0.594717[/C][C]0.810566[/C][C]0.405283[/C][/ROW]
[ROW][C]75[/C][C]0.568977[/C][C]0.862045[/C][C]0.431023[/C][/ROW]
[ROW][C]76[/C][C]0.579438[/C][C]0.841123[/C][C]0.420562[/C][/ROW]
[ROW][C]77[/C][C]0.690524[/C][C]0.618951[/C][C]0.309476[/C][/ROW]
[ROW][C]78[/C][C]0.664579[/C][C]0.670843[/C][C]0.335421[/C][/ROW]
[ROW][C]79[/C][C]0.650071[/C][C]0.699858[/C][C]0.349929[/C][/ROW]
[ROW][C]80[/C][C]0.630961[/C][C]0.738077[/C][C]0.369039[/C][/ROW]
[ROW][C]81[/C][C]0.628546[/C][C]0.742909[/C][C]0.371454[/C][/ROW]
[ROW][C]82[/C][C]0.59844[/C][C]0.80312[/C][C]0.40156[/C][/ROW]
[ROW][C]83[/C][C]0.650977[/C][C]0.698046[/C][C]0.349023[/C][/ROW]
[ROW][C]84[/C][C]0.62322[/C][C]0.75356[/C][C]0.37678[/C][/ROW]
[ROW][C]85[/C][C]0.65728[/C][C]0.68544[/C][C]0.34272[/C][/ROW]
[ROW][C]86[/C][C]0.628822[/C][C]0.742355[/C][C]0.371178[/C][/ROW]
[ROW][C]87[/C][C]0.725116[/C][C]0.549769[/C][C]0.274884[/C][/ROW]
[ROW][C]88[/C][C]0.710656[/C][C]0.578687[/C][C]0.289344[/C][/ROW]
[ROW][C]89[/C][C]0.683879[/C][C]0.632243[/C][C]0.316121[/C][/ROW]
[ROW][C]90[/C][C]0.652566[/C][C]0.694868[/C][C]0.347434[/C][/ROW]
[ROW][C]91[/C][C]0.627724[/C][C]0.744552[/C][C]0.372276[/C][/ROW]
[ROW][C]92[/C][C]0.629145[/C][C]0.74171[/C][C]0.370855[/C][/ROW]
[ROW][C]93[/C][C]0.657912[/C][C]0.684176[/C][C]0.342088[/C][/ROW]
[ROW][C]94[/C][C]0.669475[/C][C]0.66105[/C][C]0.330525[/C][/ROW]
[ROW][C]95[/C][C]0.798079[/C][C]0.403842[/C][C]0.201921[/C][/ROW]
[ROW][C]96[/C][C]0.779996[/C][C]0.440008[/C][C]0.220004[/C][/ROW]
[ROW][C]97[/C][C]0.771607[/C][C]0.456787[/C][C]0.228393[/C][/ROW]
[ROW][C]98[/C][C]0.798511[/C][C]0.402978[/C][C]0.201489[/C][/ROW]
[ROW][C]99[/C][C]0.784638[/C][C]0.430725[/C][C]0.215362[/C][/ROW]
[ROW][C]100[/C][C]0.813815[/C][C]0.372371[/C][C]0.186185[/C][/ROW]
[ROW][C]101[/C][C]0.801304[/C][C]0.397392[/C][C]0.198696[/C][/ROW]
[ROW][C]102[/C][C]0.841981[/C][C]0.316037[/C][C]0.158019[/C][/ROW]
[ROW][C]103[/C][C]0.889967[/C][C]0.220065[/C][C]0.110033[/C][/ROW]
[ROW][C]104[/C][C]0.877998[/C][C]0.244004[/C][C]0.122002[/C][/ROW]
[ROW][C]105[/C][C]0.865846[/C][C]0.268309[/C][C]0.134154[/C][/ROW]
[ROW][C]106[/C][C]0.862146[/C][C]0.275707[/C][C]0.137854[/C][/ROW]
[ROW][C]107[/C][C]0.868436[/C][C]0.263128[/C][C]0.131564[/C][/ROW]
[ROW][C]108[/C][C]0.889731[/C][C]0.220539[/C][C]0.110269[/C][/ROW]
[ROW][C]109[/C][C]0.891871[/C][C]0.216259[/C][C]0.108129[/C][/ROW]
[ROW][C]110[/C][C]0.895545[/C][C]0.20891[/C][C]0.104455[/C][/ROW]
[ROW][C]111[/C][C]0.950042[/C][C]0.0999166[/C][C]0.0499583[/C][/ROW]
[ROW][C]112[/C][C]0.96831[/C][C]0.0633805[/C][C]0.0316903[/C][/ROW]
[ROW][C]113[/C][C]0.968996[/C][C]0.0620083[/C][C]0.0310042[/C][/ROW]
[ROW][C]114[/C][C]0.96614[/C][C]0.06772[/C][C]0.03386[/C][/ROW]
[ROW][C]115[/C][C]0.962575[/C][C]0.0748493[/C][C]0.0374247[/C][/ROW]
[ROW][C]116[/C][C]0.976393[/C][C]0.0472142[/C][C]0.0236071[/C][/ROW]
[ROW][C]117[/C][C]0.98038[/C][C]0.0392406[/C][C]0.0196203[/C][/ROW]
[ROW][C]118[/C][C]0.985664[/C][C]0.0286723[/C][C]0.0143362[/C][/ROW]
[ROW][C]119[/C][C]0.988958[/C][C]0.0220832[/C][C]0.0110416[/C][/ROW]
[ROW][C]120[/C][C]0.986988[/C][C]0.0260249[/C][C]0.0130125[/C][/ROW]
[ROW][C]121[/C][C]0.991291[/C][C]0.0174183[/C][C]0.00870916[/C][/ROW]
[ROW][C]122[/C][C]0.990352[/C][C]0.0192962[/C][C]0.00964809[/C][/ROW]
[ROW][C]123[/C][C]0.991414[/C][C]0.0171729[/C][C]0.00858644[/C][/ROW]
[ROW][C]124[/C][C]0.992234[/C][C]0.0155327[/C][C]0.00776637[/C][/ROW]
[ROW][C]125[/C][C]0.995452[/C][C]0.00909673[/C][C]0.00454836[/C][/ROW]
[ROW][C]126[/C][C]0.994436[/C][C]0.0111283[/C][C]0.00556416[/C][/ROW]
[ROW][C]127[/C][C]0.997551[/C][C]0.00489794[/C][C]0.00244897[/C][/ROW]
[ROW][C]128[/C][C]0.997829[/C][C]0.00434181[/C][C]0.00217091[/C][/ROW]
[ROW][C]129[/C][C]0.997164[/C][C]0.00567274[/C][C]0.00283637[/C][/ROW]
[ROW][C]130[/C][C]0.99675[/C][C]0.00650072[/C][C]0.00325036[/C][/ROW]
[ROW][C]131[/C][C]0.996452[/C][C]0.0070962[/C][C]0.0035481[/C][/ROW]
[ROW][C]132[/C][C]0.99572[/C][C]0.00856022[/C][C]0.00428011[/C][/ROW]
[ROW][C]133[/C][C]0.995017[/C][C]0.00996664[/C][C]0.00498332[/C][/ROW]
[ROW][C]134[/C][C]0.993942[/C][C]0.0121168[/C][C]0.0060584[/C][/ROW]
[ROW][C]135[/C][C]0.992855[/C][C]0.0142892[/C][C]0.00714462[/C][/ROW]
[ROW][C]136[/C][C]0.99376[/C][C]0.01248[/C][C]0.00624002[/C][/ROW]
[ROW][C]137[/C][C]0.992443[/C][C]0.015114[/C][C]0.00755699[/C][/ROW]
[ROW][C]138[/C][C]0.990815[/C][C]0.0183697[/C][C]0.00918483[/C][/ROW]
[ROW][C]139[/C][C]0.989128[/C][C]0.0217447[/C][C]0.0108724[/C][/ROW]
[ROW][C]140[/C][C]0.991405[/C][C]0.01719[/C][C]0.00859499[/C][/ROW]
[ROW][C]141[/C][C]0.9937[/C][C]0.0126006[/C][C]0.00630032[/C][/ROW]
[ROW][C]142[/C][C]0.992172[/C][C]0.015657[/C][C]0.00782849[/C][/ROW]
[ROW][C]143[/C][C]0.990153[/C][C]0.0196934[/C][C]0.00984669[/C][/ROW]
[ROW][C]144[/C][C]0.988432[/C][C]0.0231364[/C][C]0.0115682[/C][/ROW]
[ROW][C]145[/C][C]0.99183[/C][C]0.0163398[/C][C]0.00816992[/C][/ROW]
[ROW][C]146[/C][C]0.989988[/C][C]0.0200242[/C][C]0.0100121[/C][/ROW]
[ROW][C]147[/C][C]0.989912[/C][C]0.0201752[/C][C]0.0100876[/C][/ROW]
[ROW][C]148[/C][C]0.989069[/C][C]0.0218616[/C][C]0.0109308[/C][/ROW]
[ROW][C]149[/C][C]0.986504[/C][C]0.026992[/C][C]0.013496[/C][/ROW]
[ROW][C]150[/C][C]0.984448[/C][C]0.0311039[/C][C]0.0155519[/C][/ROW]
[ROW][C]151[/C][C]0.982216[/C][C]0.0355676[/C][C]0.0177838[/C][/ROW]
[ROW][C]152[/C][C]0.980001[/C][C]0.0399989[/C][C]0.0199995[/C][/ROW]
[ROW][C]153[/C][C]0.975791[/C][C]0.0484178[/C][C]0.0242089[/C][/ROW]
[ROW][C]154[/C][C]0.977971[/C][C]0.0440576[/C][C]0.0220288[/C][/ROW]
[ROW][C]155[/C][C]0.974669[/C][C]0.0506627[/C][C]0.0253313[/C][/ROW]
[ROW][C]156[/C][C]0.988085[/C][C]0.0238303[/C][C]0.0119152[/C][/ROW]
[ROW][C]157[/C][C]0.986361[/C][C]0.027278[/C][C]0.013639[/C][/ROW]
[ROW][C]158[/C][C]0.984481[/C][C]0.0310373[/C][C]0.0155187[/C][/ROW]
[ROW][C]159[/C][C]0.980634[/C][C]0.0387329[/C][C]0.0193664[/C][/ROW]
[ROW][C]160[/C][C]0.982699[/C][C]0.0346024[/C][C]0.0173012[/C][/ROW]
[ROW][C]161[/C][C]0.978884[/C][C]0.042231[/C][C]0.0211155[/C][/ROW]
[ROW][C]162[/C][C]0.975648[/C][C]0.0487037[/C][C]0.0243518[/C][/ROW]
[ROW][C]163[/C][C]0.974139[/C][C]0.0517223[/C][C]0.0258611[/C][/ROW]
[ROW][C]164[/C][C]0.97271[/C][C]0.0545793[/C][C]0.0272897[/C][/ROW]
[ROW][C]165[/C][C]0.96828[/C][C]0.0634396[/C][C]0.0317198[/C][/ROW]
[ROW][C]166[/C][C]0.974311[/C][C]0.0513783[/C][C]0.0256891[/C][/ROW]
[ROW][C]167[/C][C]0.968993[/C][C]0.0620133[/C][C]0.0310067[/C][/ROW]
[ROW][C]168[/C][C]0.966097[/C][C]0.067805[/C][C]0.0339025[/C][/ROW]
[ROW][C]169[/C][C]0.981722[/C][C]0.0365569[/C][C]0.0182785[/C][/ROW]
[ROW][C]170[/C][C]0.982602[/C][C]0.0347961[/C][C]0.017398[/C][/ROW]
[ROW][C]171[/C][C]0.981116[/C][C]0.037768[/C][C]0.018884[/C][/ROW]
[ROW][C]172[/C][C]0.977604[/C][C]0.0447925[/C][C]0.0223962[/C][/ROW]
[ROW][C]173[/C][C]0.982807[/C][C]0.0343867[/C][C]0.0171934[/C][/ROW]
[ROW][C]174[/C][C]0.97865[/C][C]0.0426994[/C][C]0.0213497[/C][/ROW]
[ROW][C]175[/C][C]0.978656[/C][C]0.0426882[/C][C]0.0213441[/C][/ROW]
[ROW][C]176[/C][C]0.973562[/C][C]0.052876[/C][C]0.026438[/C][/ROW]
[ROW][C]177[/C][C]0.97813[/C][C]0.0437399[/C][C]0.02187[/C][/ROW]
[ROW][C]178[/C][C]0.973939[/C][C]0.052123[/C][C]0.0260615[/C][/ROW]
[ROW][C]179[/C][C]0.968172[/C][C]0.0636559[/C][C]0.031828[/C][/ROW]
[ROW][C]180[/C][C]0.961004[/C][C]0.0779922[/C][C]0.0389961[/C][/ROW]
[ROW][C]181[/C][C]0.963663[/C][C]0.0726734[/C][C]0.0363367[/C][/ROW]
[ROW][C]182[/C][C]0.959897[/C][C]0.0802056[/C][C]0.0401028[/C][/ROW]
[ROW][C]183[/C][C]0.958287[/C][C]0.0834251[/C][C]0.0417125[/C][/ROW]
[ROW][C]184[/C][C]0.952623[/C][C]0.0947545[/C][C]0.0473772[/C][/ROW]
[ROW][C]185[/C][C]0.956551[/C][C]0.0868978[/C][C]0.0434489[/C][/ROW]
[ROW][C]186[/C][C]0.958279[/C][C]0.0834421[/C][C]0.0417211[/C][/ROW]
[ROW][C]187[/C][C]0.949913[/C][C]0.100173[/C][C]0.0500867[/C][/ROW]
[ROW][C]188[/C][C]0.94415[/C][C]0.1117[/C][C]0.0558498[/C][/ROW]
[ROW][C]189[/C][C]0.934096[/C][C]0.131807[/C][C]0.0659037[/C][/ROW]
[ROW][C]190[/C][C]0.94188[/C][C]0.116241[/C][C]0.0581204[/C][/ROW]
[ROW][C]191[/C][C]0.931505[/C][C]0.13699[/C][C]0.0684949[/C][/ROW]
[ROW][C]192[/C][C]0.951594[/C][C]0.0968117[/C][C]0.0484059[/C][/ROW]
[ROW][C]193[/C][C]0.945282[/C][C]0.109437[/C][C]0.0547184[/C][/ROW]
[ROW][C]194[/C][C]0.937094[/C][C]0.125813[/C][C]0.0629064[/C][/ROW]
[ROW][C]195[/C][C]0.925401[/C][C]0.149198[/C][C]0.0745988[/C][/ROW]
[ROW][C]196[/C][C]0.910774[/C][C]0.178452[/C][C]0.0892262[/C][/ROW]
[ROW][C]197[/C][C]0.909194[/C][C]0.181613[/C][C]0.0908065[/C][/ROW]
[ROW][C]198[/C][C]0.917835[/C][C]0.16433[/C][C]0.082165[/C][/ROW]
[ROW][C]199[/C][C]0.931529[/C][C]0.136941[/C][C]0.0684705[/C][/ROW]
[ROW][C]200[/C][C]0.920532[/C][C]0.158935[/C][C]0.0794675[/C][/ROW]
[ROW][C]201[/C][C]0.905874[/C][C]0.188252[/C][C]0.0941259[/C][/ROW]
[ROW][C]202[/C][C]0.918881[/C][C]0.162237[/C][C]0.0811186[/C][/ROW]
[ROW][C]203[/C][C]0.90473[/C][C]0.190541[/C][C]0.0952704[/C][/ROW]
[ROW][C]204[/C][C]0.917529[/C][C]0.164942[/C][C]0.0824712[/C][/ROW]
[ROW][C]205[/C][C]0.905949[/C][C]0.188101[/C][C]0.0940506[/C][/ROW]
[ROW][C]206[/C][C]0.888418[/C][C]0.223164[/C][C]0.111582[/C][/ROW]
[ROW][C]207[/C][C]0.876496[/C][C]0.247008[/C][C]0.123504[/C][/ROW]
[ROW][C]208[/C][C]0.861219[/C][C]0.277563[/C][C]0.138781[/C][/ROW]
[ROW][C]209[/C][C]0.84717[/C][C]0.30566[/C][C]0.15283[/C][/ROW]
[ROW][C]210[/C][C]0.828581[/C][C]0.342837[/C][C]0.171419[/C][/ROW]
[ROW][C]211[/C][C]0.831967[/C][C]0.336066[/C][C]0.168033[/C][/ROW]
[ROW][C]212[/C][C]0.818409[/C][C]0.363181[/C][C]0.181591[/C][/ROW]
[ROW][C]213[/C][C]0.815549[/C][C]0.368902[/C][C]0.184451[/C][/ROW]
[ROW][C]214[/C][C]0.785767[/C][C]0.428465[/C][C]0.214233[/C][/ROW]
[ROW][C]215[/C][C]0.773617[/C][C]0.452767[/C][C]0.226383[/C][/ROW]
[ROW][C]216[/C][C]0.74351[/C][C]0.51298[/C][C]0.25649[/C][/ROW]
[ROW][C]217[/C][C]0.724075[/C][C]0.551851[/C][C]0.275925[/C][/ROW]
[ROW][C]218[/C][C]0.686952[/C][C]0.626097[/C][C]0.313048[/C][/ROW]
[ROW][C]219[/C][C]0.689467[/C][C]0.621066[/C][C]0.310533[/C][/ROW]
[ROW][C]220[/C][C]0.660145[/C][C]0.679709[/C][C]0.339855[/C][/ROW]
[ROW][C]221[/C][C]0.634255[/C][C]0.731489[/C][C]0.365745[/C][/ROW]
[ROW][C]222[/C][C]0.599557[/C][C]0.800886[/C][C]0.400443[/C][/ROW]
[ROW][C]223[/C][C]0.573439[/C][C]0.853122[/C][C]0.426561[/C][/ROW]
[ROW][C]224[/C][C]0.528827[/C][C]0.942346[/C][C]0.471173[/C][/ROW]
[ROW][C]225[/C][C]0.507823[/C][C]0.984355[/C][C]0.492177[/C][/ROW]
[ROW][C]226[/C][C]0.46516[/C][C]0.930321[/C][C]0.53484[/C][/ROW]
[ROW][C]227[/C][C]0.420878[/C][C]0.841756[/C][C]0.579122[/C][/ROW]
[ROW][C]228[/C][C]0.392742[/C][C]0.785483[/C][C]0.607258[/C][/ROW]
[ROW][C]229[/C][C]0.380939[/C][C]0.761878[/C][C]0.619061[/C][/ROW]
[ROW][C]230[/C][C]0.33748[/C][C]0.67496[/C][C]0.66252[/C][/ROW]
[ROW][C]231[/C][C]0.311469[/C][C]0.622937[/C][C]0.688531[/C][/ROW]
[ROW][C]232[/C][C]0.327762[/C][C]0.655523[/C][C]0.672238[/C][/ROW]
[ROW][C]233[/C][C]0.370467[/C][C]0.740934[/C][C]0.629533[/C][/ROW]
[ROW][C]234[/C][C]0.358505[/C][C]0.71701[/C][C]0.641495[/C][/ROW]
[ROW][C]235[/C][C]0.407786[/C][C]0.815571[/C][C]0.592214[/C][/ROW]
[ROW][C]236[/C][C]0.370838[/C][C]0.741675[/C][C]0.629162[/C][/ROW]
[ROW][C]237[/C][C]0.37314[/C][C]0.74628[/C][C]0.62686[/C][/ROW]
[ROW][C]238[/C][C]0.462546[/C][C]0.925093[/C][C]0.537454[/C][/ROW]
[ROW][C]239[/C][C]0.413996[/C][C]0.827993[/C][C]0.586004[/C][/ROW]
[ROW][C]240[/C][C]0.384666[/C][C]0.769331[/C][C]0.615334[/C][/ROW]
[ROW][C]241[/C][C]0.353397[/C][C]0.706795[/C][C]0.646603[/C][/ROW]
[ROW][C]242[/C][C]0.3205[/C][C]0.641[/C][C]0.6795[/C][/ROW]
[ROW][C]243[/C][C]0.578781[/C][C]0.842437[/C][C]0.421219[/C][/ROW]
[ROW][C]244[/C][C]0.569346[/C][C]0.861308[/C][C]0.430654[/C][/ROW]
[ROW][C]245[/C][C]0.541367[/C][C]0.917266[/C][C]0.458633[/C][/ROW]
[ROW][C]246[/C][C]0.485081[/C][C]0.970161[/C][C]0.514919[/C][/ROW]
[ROW][C]247[/C][C]0.44367[/C][C]0.887341[/C][C]0.55633[/C][/ROW]
[ROW][C]248[/C][C]0.421225[/C][C]0.842449[/C][C]0.578775[/C][/ROW]
[ROW][C]249[/C][C]0.3845[/C][C]0.768999[/C][C]0.6155[/C][/ROW]
[ROW][C]250[/C][C]0.343121[/C][C]0.686241[/C][C]0.656879[/C][/ROW]
[ROW][C]251[/C][C]0.330906[/C][C]0.661812[/C][C]0.669094[/C][/ROW]
[ROW][C]252[/C][C]0.387229[/C][C]0.774459[/C][C]0.612771[/C][/ROW]
[ROW][C]253[/C][C]0.373676[/C][C]0.747351[/C][C]0.626324[/C][/ROW]
[ROW][C]254[/C][C]0.315612[/C][C]0.631224[/C][C]0.684388[/C][/ROW]
[ROW][C]255[/C][C]0.261985[/C][C]0.523969[/C][C]0.738015[/C][/ROW]
[ROW][C]256[/C][C]0.209831[/C][C]0.419662[/C][C]0.790169[/C][/ROW]
[ROW][C]257[/C][C]0.202389[/C][C]0.404779[/C][C]0.797611[/C][/ROW]
[ROW][C]258[/C][C]0.156026[/C][C]0.312051[/C][C]0.843974[/C][/ROW]
[ROW][C]259[/C][C]0.14097[/C][C]0.28194[/C][C]0.85903[/C][/ROW]
[ROW][C]260[/C][C]0.111263[/C][C]0.222525[/C][C]0.888737[/C][/ROW]
[ROW][C]261[/C][C]0.0809815[/C][C]0.161963[/C][C]0.919019[/C][/ROW]
[ROW][C]262[/C][C]0.0837168[/C][C]0.167434[/C][C]0.916283[/C][/ROW]
[ROW][C]263[/C][C]0.0556105[/C][C]0.111221[/C][C]0.944389[/C][/ROW]
[ROW][C]264[/C][C]0.0398098[/C][C]0.0796195[/C][C]0.96019[/C][/ROW]
[ROW][C]265[/C][C]0.0477781[/C][C]0.0955562[/C][C]0.952222[/C][/ROW]
[ROW][C]266[/C][C]0.684511[/C][C]0.630979[/C][C]0.315489[/C][/ROW]
[ROW][C]267[/C][C]0.763087[/C][C]0.473827[/C][C]0.236913[/C][/ROW]
[ROW][C]268[/C][C]0.940811[/C][C]0.118379[/C][C]0.0591894[/C][/ROW]
[ROW][C]269[/C][C]0.991889[/C][C]0.0162222[/C][C]0.00811108[/C][/ROW]
[ROW][C]270[/C][C]0.97768[/C][C]0.0446403[/C][C]0.0223201[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268065&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268065&T=5

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
17	0.312658	0.625317	0.687342
18	0.294718	0.589437	0.705282
19	0.176886	0.353772	0.823114
20	0.0993071	0.198614	0.900693
21	0.248041	0.496081	0.751959
22	0.171144	0.342289	0.828856
23	0.109204	0.218408	0.890796
24	0.0966523	0.193305	0.903348
25	0.0679891	0.135978	0.932011
26	0.0804227	0.160845	0.919577
27	0.0518832	0.103766	0.948117
28	0.0419219	0.0838438	0.958078
29	0.0319409	0.0638818	0.968059
30	0.0199673	0.0399345	0.980033
31	0.0120553	0.0241105	0.987945
32	0.0161707	0.0323415	0.983829
33	0.0103584	0.0207168	0.989642
34	0.00774815	0.0154963	0.992252
35	0.00472332	0.00944663	0.995277
36	0.0932805	0.186561	0.906719
37	0.0852894	0.170579	0.914711
38	0.125584	0.251169	0.874416
39	0.0958724	0.191745	0.904128
40	0.0794964	0.158993	0.920504
41	0.182759	0.365517	0.817241
42	0.17815	0.356299	0.82185
43	0.308503	0.617006	0.691497
44	0.321147	0.642293	0.678853
45	0.297046	0.594091	0.702954
46	0.268211	0.536422	0.731789
47	0.226412	0.452823	0.773588
48	0.200417	0.400835	0.799583
49	0.192827	0.385654	0.807173
50	0.218451	0.436903	0.781549
51	0.281262	0.562524	0.718738
52	0.343037	0.686074	0.656963
53	0.314458	0.628915	0.685542
54	0.380118	0.760236	0.619882
55	0.386049	0.772099	0.613951
56	0.452245	0.904489	0.547755
57	0.511635	0.97673	0.488365
58	0.477964	0.955927	0.522036
59	0.61709	0.765819	0.38291
60	0.638287	0.723427	0.361713
61	0.596591	0.806818	0.403409
62	0.649668	0.700663	0.350332
63	0.640951	0.718097	0.359049
64	0.618572	0.762857	0.381428
65	0.720703	0.558593	0.279297
66	0.764218	0.471564	0.235782
67	0.755861	0.488278	0.244139
68	0.731601	0.536799	0.268399
69	0.710042	0.579916	0.289958
70	0.682323	0.635354	0.317677
71	0.677805	0.64439	0.322195
72	0.654428	0.691143	0.345572
73	0.633123	0.733753	0.366877
74	0.594717	0.810566	0.405283
75	0.568977	0.862045	0.431023
76	0.579438	0.841123	0.420562
77	0.690524	0.618951	0.309476
78	0.664579	0.670843	0.335421
79	0.650071	0.699858	0.349929
80	0.630961	0.738077	0.369039
81	0.628546	0.742909	0.371454
82	0.59844	0.80312	0.40156
83	0.650977	0.698046	0.349023
84	0.62322	0.75356	0.37678
85	0.65728	0.68544	0.34272
86	0.628822	0.742355	0.371178
87	0.725116	0.549769	0.274884
88	0.710656	0.578687	0.289344
89	0.683879	0.632243	0.316121
90	0.652566	0.694868	0.347434
91	0.627724	0.744552	0.372276
92	0.629145	0.74171	0.370855
93	0.657912	0.684176	0.342088
94	0.669475	0.66105	0.330525
95	0.798079	0.403842	0.201921
96	0.779996	0.440008	0.220004
97	0.771607	0.456787	0.228393
98	0.798511	0.402978	0.201489
99	0.784638	0.430725	0.215362
100	0.813815	0.372371	0.186185
101	0.801304	0.397392	0.198696
102	0.841981	0.316037	0.158019
103	0.889967	0.220065	0.110033
104	0.877998	0.244004	0.122002
105	0.865846	0.268309	0.134154
106	0.862146	0.275707	0.137854
107	0.868436	0.263128	0.131564
108	0.889731	0.220539	0.110269
109	0.891871	0.216259	0.108129
110	0.895545	0.20891	0.104455
111	0.950042	0.0999166	0.0499583
112	0.96831	0.0633805	0.0316903
113	0.968996	0.0620083	0.0310042
114	0.96614	0.06772	0.03386
115	0.962575	0.0748493	0.0374247
116	0.976393	0.0472142	0.0236071
117	0.98038	0.0392406	0.0196203
118	0.985664	0.0286723	0.0143362
119	0.988958	0.0220832	0.0110416
120	0.986988	0.0260249	0.0130125
121	0.991291	0.0174183	0.00870916
122	0.990352	0.0192962	0.00964809
123	0.991414	0.0171729	0.00858644
124	0.992234	0.0155327	0.00776637
125	0.995452	0.00909673	0.00454836
126	0.994436	0.0111283	0.00556416
127	0.997551	0.00489794	0.00244897
128	0.997829	0.00434181	0.00217091
129	0.997164	0.00567274	0.00283637
130	0.99675	0.00650072	0.00325036
131	0.996452	0.0070962	0.0035481
132	0.99572	0.00856022	0.00428011
133	0.995017	0.00996664	0.00498332
134	0.993942	0.0121168	0.0060584
135	0.992855	0.0142892	0.00714462
136	0.99376	0.01248	0.00624002
137	0.992443	0.015114	0.00755699
138	0.990815	0.0183697	0.00918483
139	0.989128	0.0217447	0.0108724
140	0.991405	0.01719	0.00859499
141	0.9937	0.0126006	0.00630032
142	0.992172	0.015657	0.00782849
143	0.990153	0.0196934	0.00984669
144	0.988432	0.0231364	0.0115682
145	0.99183	0.0163398	0.00816992
146	0.989988	0.0200242	0.0100121
147	0.989912	0.0201752	0.0100876
148	0.989069	0.0218616	0.0109308
149	0.986504	0.026992	0.013496
150	0.984448	0.0311039	0.0155519
151	0.982216	0.0355676	0.0177838
152	0.980001	0.0399989	0.0199995
153	0.975791	0.0484178	0.0242089
154	0.977971	0.0440576	0.0220288
155	0.974669	0.0506627	0.0253313
156	0.988085	0.0238303	0.0119152
157	0.986361	0.027278	0.013639
158	0.984481	0.0310373	0.0155187
159	0.980634	0.0387329	0.0193664
160	0.982699	0.0346024	0.0173012
161	0.978884	0.042231	0.0211155
162	0.975648	0.0487037	0.0243518
163	0.974139	0.0517223	0.0258611
164	0.97271	0.0545793	0.0272897
165	0.96828	0.0634396	0.0317198
166	0.974311	0.0513783	0.0256891
167	0.968993	0.0620133	0.0310067
168	0.966097	0.067805	0.0339025
169	0.981722	0.0365569	0.0182785
170	0.982602	0.0347961	0.017398
171	0.981116	0.037768	0.018884
172	0.977604	0.0447925	0.0223962
173	0.982807	0.0343867	0.0171934
174	0.97865	0.0426994	0.0213497
175	0.978656	0.0426882	0.0213441
176	0.973562	0.052876	0.026438
177	0.97813	0.0437399	0.02187
178	0.973939	0.052123	0.0260615
179	0.968172	0.0636559	0.031828
180	0.961004	0.0779922	0.0389961
181	0.963663	0.0726734	0.0363367
182	0.959897	0.0802056	0.0401028
183	0.958287	0.0834251	0.0417125
184	0.952623	0.0947545	0.0473772
185	0.956551	0.0868978	0.0434489
186	0.958279	0.0834421	0.0417211
187	0.949913	0.100173	0.0500867
188	0.94415	0.1117	0.0558498
189	0.934096	0.131807	0.0659037
190	0.94188	0.116241	0.0581204
191	0.931505	0.13699	0.0684949
192	0.951594	0.0968117	0.0484059
193	0.945282	0.109437	0.0547184
194	0.937094	0.125813	0.0629064
195	0.925401	0.149198	0.0745988
196	0.910774	0.178452	0.0892262
197	0.909194	0.181613	0.0908065
198	0.917835	0.16433	0.082165
199	0.931529	0.136941	0.0684705
200	0.920532	0.158935	0.0794675
201	0.905874	0.188252	0.0941259
202	0.918881	0.162237	0.0811186
203	0.90473	0.190541	0.0952704
204	0.917529	0.164942	0.0824712
205	0.905949	0.188101	0.0940506
206	0.888418	0.223164	0.111582
207	0.876496	0.247008	0.123504
208	0.861219	0.277563	0.138781
209	0.84717	0.30566	0.15283
210	0.828581	0.342837	0.171419
211	0.831967	0.336066	0.168033
212	0.818409	0.363181	0.181591
213	0.815549	0.368902	0.184451
214	0.785767	0.428465	0.214233
215	0.773617	0.452767	0.226383
216	0.74351	0.51298	0.25649
217	0.724075	0.551851	0.275925
218	0.686952	0.626097	0.313048
219	0.689467	0.621066	0.310533
220	0.660145	0.679709	0.339855
221	0.634255	0.731489	0.365745
222	0.599557	0.800886	0.400443
223	0.573439	0.853122	0.426561
224	0.528827	0.942346	0.471173
225	0.507823	0.984355	0.492177
226	0.46516	0.930321	0.53484
227	0.420878	0.841756	0.579122
228	0.392742	0.785483	0.607258
229	0.380939	0.761878	0.619061
230	0.33748	0.67496	0.66252
231	0.311469	0.622937	0.688531
232	0.327762	0.655523	0.672238
233	0.370467	0.740934	0.629533
234	0.358505	0.71701	0.641495
235	0.407786	0.815571	0.592214
236	0.370838	0.741675	0.629162
237	0.37314	0.74628	0.62686
238	0.462546	0.925093	0.537454
239	0.413996	0.827993	0.586004
240	0.384666	0.769331	0.615334
241	0.353397	0.706795	0.646603
242	0.3205	0.641	0.6795
243	0.578781	0.842437	0.421219
244	0.569346	0.861308	0.430654
245	0.541367	0.917266	0.458633
246	0.485081	0.970161	0.514919
247	0.44367	0.887341	0.55633
248	0.421225	0.842449	0.578775
249	0.3845	0.768999	0.6155
250	0.343121	0.686241	0.656879
251	0.330906	0.661812	0.669094
252	0.387229	0.774459	0.612771
253	0.373676	0.747351	0.626324
254	0.315612	0.631224	0.684388
255	0.261985	0.523969	0.738015
256	0.209831	0.419662	0.790169
257	0.202389	0.404779	0.797611
258	0.156026	0.312051	0.843974
259	0.14097	0.28194	0.85903
260	0.111263	0.222525	0.888737
261	0.0809815	0.161963	0.919019
262	0.0837168	0.167434	0.916283
263	0.0556105	0.111221	0.944389
264	0.0398098	0.0796195	0.96019
265	0.0477781	0.0955562	0.952222
266	0.684511	0.630979	0.315489
267	0.763087	0.473827	0.236913
268	0.940811	0.118379	0.0591894
269	0.991889	0.0162222	0.00811108
270	0.97768	0.0446403	0.0223201

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	9	0.0354331	NOK
5% type I error level	62	0.244094	NOK
10% type I error level	89	0.350394	NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 9 & 0.0354331 & NOK \tabularnewline
5% type I error level & 62 & 0.244094 & NOK \tabularnewline
10% type I error level & 89 & 0.350394 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268065&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]9[/C][C]0.0354331[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]62[/C][C]0.244094[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]89[/C][C]0.350394[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268065&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268065&T=6

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	9	0.0354331	NOK
5% type I error level	62	0.244094	NOK
10% type I error level	89	0.350394	NOK

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Figure 8

PNG link

Postscript link

PDF link

Figure 9

PNG link

Postscript link

PDF link

Figure 10

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code